Gyrification and neural connectivity in schizophrenia
TONYAWHITEa,bAND CLAUS C. HILGETAGc,d
aErasmus Medical Centre, Rotterdam;bUniversity of Minnesota;cJacobs University Bremen; anddBoston University
thought to be established during brain development through the shaping influences of tension exerted by viscoelastic nerve fibers. The tension-based
morphogenesis results in compact wiring that enhances efficient neural processing. Individuals with schizophrenia present with multiple symptoms that can
include impaired thought, action, perception, and cognition. The global nature of these symptoms has led researchers to explore a more global disruption
the organization of neural connectivity, then a disruption in neural connectivity may also alter the surface morphology of the brain. This paper reviews
developmental theories of gyrification and the potential interaction between gyrification and neuronal connectivity. Studies of gyrification abnormalities in
children,adolescents,and adults withschizophreniademonstratea relationshipbetween disruptedfunctionand alteredmorphologyinthesurfacepatternsofthe
cerebral cortex. This altered form may provide helpful clues in understanding the neurobiological abnormalities associated with schizophrenia.
Schizophrenia is associated with a diverse array of clinical
symptoms and cognitive deficits (Addington, Addington &
Maticka-Tyndale, 1991; Andreasen et al., 1999; Johnstone,
Owens, Frith, & Crow, 1987). The symptoms include hal-
lucinations, delusions, disorganized thought and speech, and
negative symptoms such as avolition, alogia, and flattened
affect (Andreasen & Olsen, 1982). In addition to the clinical
symptoms, there are often cognitive deficits that span multi-
ple neuropsychological domains (White, Ho, Ward, Leary,
& Andreasen, 2006). The diversity of these symptoms sug-
gests perturbations that act on global scales of brain function.
As the brain operates through an orchestration of intricately
tunedneural networks, adisruption intheconnectivity within
or between these networks is one of the leading hypotheses
underlying schizophrenia (Andreasen, Paradiso, & O’Leary,
1998; Friston, 1998; Konrad & Winterer, 2008; Weinberger,
Berman, Suddath, & Torrey, 1992). Evidence supporting this
theory has emerged through post mortem (Benes, 1989; Col-
ter et al., 1987; Davis et al., 2003; Heckers, Heinsen, Geiger,
& Beckmann, 1991), genetic (Hakaket al., 2001), and neuro-
imaging studies (Agartz, Andersson, & Skare, 2001; Arde-
kani,Neirenberg, Hoptman, Javitt, &Lim, 2003; Buchsbaum
et al., 1998; Kendi et al., 2008; Kubicki et al., 2007; Kumra
et al.,2004,2005; Lim et al., 1999; Rose et al., 2006; Volkow
et al., 1988; White et al., 2007).
Theories of aberrant connectivity in distributed neural net-
works in schizophrenia have paralleled, and perhaps even
brainconnectivity. Measures ofneuralconnectivityaredivided
into structural, functional, and effective connectivity, each
which evaluates a different aspect of connectivity, although
these aspects are interrelated. Structural connectivity refers to
measures of the physical presence and pathways of the actual
neural fibers. It is commonly established in animal models
through anatomical tract tracing techniques (Ko ¨bbert et al.,
2000), or less reliably in noninvasive human studies utilizing
techniques such as diffusion tensor imaging (DTI; Shimony,
Snyder, Conturo, & Corbetta, 2004). Although the structural
connectivityof the human brain is not directlyknown, because
state,” have been taken as a proxy for human anatomical con-
nections (Greicius, Supekar, Menon, & Dougherty, 2009).
tween brain regions that possess correlated temporal activation
patterns (Friston, 1994), as demonstrated by various functional
tivity are linked through effective connectivity, which reflects
the causal influence of the activity in one brain region on an-
other. Thus, although functional connectivity is essentially
model free, effective connectivity relies on a model that ex-
plains how functional connectivity is mediated by structural
connectivity (Friston, 1994).
Address correspondence and reprint requests to: Tonya White, Afdeling
Postbus 2060, Rotterdam 3000 CB, The Netherlands; E-mail: t.white@
Support for this work was provided through NIMH Grant MH068540, a ju-
nior investigatoraward through the Blowitz–Ridgeway Foundation, the Essel
Foundation through the National Alliance for Research in Schizophrenia and
Affective Disorders, and the Mind Research Network. We thank the anon-
ymous reviewers for their very helpful comments and suggestions.
Development and Psychopathology 23 (2011), 339–352
#Cambridge University Press 2011
The triad of structural (Konrad & Winterer, 2008; Kubicki
berg et al., 2001, 2005; Micheloyannis et al., 2006), and effec-
& Weinberger, 2003) connectivity has been shown to be aber-
rant in patients with schizophrenia. Early positron emission to-
mography studies demonstrated regional abnormalities (Vol-
kow et al., 1988), suggesting that the impairment is focused
on specific neural subnetworks, such as hippocampal–prefron-
tal and cortical–cerebellar–thalamic–cortical connectivity (An-
dreasen et al., 1999). Aberrant connectivity in schizophrenia
rie et al., 2002) and cognitive impairments (Meyer-Lindenberg
et al., 2001), and can be altered with the administration of anti-
psychotic medication (Stephan et al., 2001).
It has recently has been argued that structural connectivity
shape of the folded cerebral cortex through axonal tension
forces (Van Essen, 1997). The overall interaction of these
forces produces the characteristic convolutions of the human
brain and leads to a compact layout that optimizes the transit of
neuronal signals between brain regions (Hilgetag & Barbas,
cher, & Kretschmann, 1988). Thus, the characteristic morphol-
ogyof thebrain, with its many gyri and sulci, may correspond
responds to function, and neural function is disrupted in
schizophrenia, then is form disrupted as well? Is it possible
that buried within the fissures and folds that make up the con-
voluted landscape of the cerebral cortex exists structural evi-
The goal of this paper is to provide a review of recent evi-
of the brain in schizophrenia. We start by reviewing the devel-
opment and theories of the underlying mechanisms associated
with gyrification. We then provide a review of studies of gyri-
dence that abnormalities of gyrification may reflect abnormal-
occurs during a relativelyshort window during prenatal devel-
opment, specific changes seen in patients with schizophrenia
may help elucidate the interplay between neurodevelopment
vide an important link for understanding the relationship be-
tween brain surface morphology and connectivity.
Theories of Gyrification
By the end of the second trimester (26 weeks gestational age)
the developing brain islissencephalic, witha generallysmooth
cortical surface (Welker, 1990). Following the 26th week the
brain surface morphology changes rapidly, and by term at 40
ent. Thus, the major steps in the process of gyrification occur
growth (Neal, Takahashi, Silva, Tiao, Walsh, & Sheen, 2007).
of the brain (Piao et al., 2004). However, because even mono-
zygotic twins show considerable differences in their folding
patterns (Thompson, Cannon, et al., 2001; White, Andreasen,
ified via biological and physical self-organization, that is,
through a multitude of interactions involving biological pro-
cesses, such as regulatory metabolic cascades or anabolic
mechanical tissue tension (Hilgetag & Barbas, 2005, 2006;
nod, 2005; Van Essen, 1997; Welker, 1990).
peting volumedemands andtension between theseregions, re-
sulting in local tissue deformation (His, 1874). One school of
morphogenetic concepts of the brain suggests that regions
destined to be become sulci (Kriegstein, Noctor, & Martinez-
localized growth. This active growth could also occur in combi-
Gross Clark, 1945). This differential growth expansion of the
1975; Toro & Burnod, 2005; Van Essen, 1997; Welker, 1990).
Theories of cortical morphogenesis should also consider
the relationship between the development of brain convolu-
tions and the pruning of neuronal and synaptic connections
(Goldman-Rakic, 1980; Goldman-Rakic & Rakic, 1984). It
hasbeensuggestedthat viscoelastictension exerted bycortico-
cortical fibers (Franze, Reichenbach, & Ka ¨s, 2008) may con-
tribute to shaping cortical convolutions (Van Essen, 1997,
2007). Specifically, thistheory proposes that neuronal connec-
tivity that develops with neuronal migration during the second
ted regions closer together, forming outward bulging gyri be-
tween them, whereas more sparsely connected regions drift
apart and are separated by inward sulci. The tension, although
very small for an individual axon (Heidemann, Lamoureux,
& Buxbaum, 1995), is summed by the very large population
plained by the highly specific organization of the underlying
connectivity (Sporns, Chialvo, Kaiser, & Hilgetag, 2004).
If tension produced by neuronal connections is involved in
the mechanismsofgyrification, then changesinthe patterns of
or experimental) that alter the connectivity between brain re-
gions. Local and remote changes of gyrification have been ob-
served after experimental white-matter lesions in the develop-
ing primate brain (Goldman-Rakic, 1980; Goldman-Rakic &
Rakic, 1984). The axonal tension concept has also been sup-
T. White and C. C. Hilgetag
of war. Adapted from “Role of Mechanical Factors in the Morphologyof the Primate Cerebral Cortex,” by C. C. Hilgetag and H. Barbas, 2006, PLoS Computational Biology, 2(3),e22.Copyright 2006
International Society for Computational Biology. Adapted with permission. [A color version of this figure can be viewed online at journals.cambridge.org/dpp]
ported by recent experimental findings in the primate brain
riesof fiberprojections, withdenser fibers being straighterand
most projections following straight or only mildly curved tra-
jectories (Hilgetag & Barbas, 2006; Toro & Burnod, 2005).
In summary, starting from genetically specified parame-
ters, such as differential growth rates, various physical pro-
cesses may interact to produce and organize the surface mor-
phology of the cerebral cortex during brain development. In
particular, experimental findings support the concept of a re-
lationship between characteristic cortical convolutions and
the specific layout of cortical fiber connections.
Measures of Gyrification
There have been a number of different techniques to quantify
brain gyrification, and different approaches are used to quan-
may be considered as one characteristic feature; because sulci
can branch in complex patterns, greater sulcal depth does not
necessarily translate into a quantitative increase in other gyr-
ification measures. Other features are sulcal frequency (Narr
et al., 2001) or cortical complexity, which typically relates
an estimate of brain surface area to volume, accounting for
the two- (2-D) and three-dimensional (3-D) differences be-
tween surface area and volume measurements.
Zilles et al. (1988) utilized coronal sections of postmortem
face excluding sulci. This measure, known as the gyrification
strong et al., 1991; Zilles et al., 1988) and ontogeny (Arm-
strong, Schleicher, Omran, Curtis, & Zilles, 1995) of cortical
gyrification (see Figure 2). Brains that have a higher degree
of cortical folding yield larger values of the GI. Anterior to
ification in the prefrontal and temporal/parietal association re-
birth. It is interesting that this plateau appears to remain con-
stant across the life span, despite the rapid brain development
and changes associated with aging (Armstrong et al., 1995).
However, because developmental studies typically require
large samples, and because postmortem samples in younger
individuals are difficult to obtain, it would be beneficial for
the study of Armstrong et al. (1995) to be replicated with a
larger sample size to confirm this finding. Age-related differ-
ences in gyrification measures using magnetic resonance
et al., 1999; White, Su, Schmidt, Kao, & Sapiro et al., 2010),
val between fixation of thebrains, brainshrinkage, or thegen-
eration of brain slices may complicate direct comparisons be-
tween MRI and postmortem GI measures.
Alternative methods for measuring the surface morphol-
ogy of the brain involve regional measurements of curvature
(i.e., convexity and concavity) of the cortical surface from
MR images (Koenderink & van Doorn, 1992; Luders et al.,
2006; Magnotta et al., 1999). These methods first define atri-
angular isosurface covering a layer within the cortical rim.
outer contour (blue line online only). This yields a unitless measure that reflects a quantification of gyrification of the brain. [A color version of
this figure can be viewed online at journals.cambridge.org/dpp]
T. White and C. C. Hilgetag
Once the isosurface is constructed, the angles between vec-
tors normal to the triangular isosurfaces are used to calcu-
late the regional curvature of the cortex. These regional mea-
sures can be utilized to study regional curvature between
groups (Luders et al., 2004, 2006) oraveraged to study global
changes (Magnotta et al., 1999; Nopoulos, Flaum, O’Leary,
Andreasen, 2000; White et al., 2002).
Gyrification Abnormalities in Schizophrenia
The ability to quantify various aspects of brain surface com-
plexity has existed for decades (Thompson, Schwartz, Lin,
Khan, & Toga, 1996; Zilles et al., 1988), but there have been
relatively few studies that applied these techniques to gyrifica-
tion in schizophrenia (Table 1). The majority of these studies
have employed the traditional 2-D GI measure to evaluate dif-
ferences between patients and controls. These studies yielded
mixed results showing GIs in patients that are higher (Harris,
Yates,et al., 2004; Vogeleyet al., 2000, 2001),lower(Bonnici
et al., 2007; Kulynych, Luevano, Jones, & Weinberger, 1997;
McIntosh et al., 2009; Sallet et al., 2003; Wheeler & Harper,
2007), or no different than controls (Highley et al., 2003).
The earliest study utilized coronal MRI slices from the left
in GI in both anterior and posterior regions in nine patients
with chronic schizophrenia (Kulynych et al., 1997). Subse-
quent studies using MRI-based GI measures have replicated
the finding of reduced GI in the frontal cortex (Bonnici et al.,
caudal regions. These studies demonstrating a decrease in the
GI were all performed on patients with chronic schizophrenia.
There have been two postmortem studies of gyrification in
patients with schizophrenia. The first study found an increase
in frontal GI in a group of patients with chronic schizophrenia
(Vogeley et al., 2000). The second postmortem study focused
tire contourof the brain, thisfinding of a reducedGIin thecin-
gulate is difficult to compare to the more global GI measures.
one of the postmortem studies, has also been reported in MRI
studies of the frontal cortex in patients with chronic (Falkai
et al.,2007; Vogeleyetal.,2001)andfirst-episodeschizophre-
nia (Harris, Yates, et al., 2004). Moreover, increased GI has
been identified in temporal lobe structures (Harris, Yates, et al.,
2004), but not occipitoparietal regions (Falkai et al., 2007;
Harris, Yates, et al., 2004). However, findings of lower GI
(Bonnici et al., 2007; McIntosh et al., 2009) have also been
reported and include studies using the same techniques that
reported an increase in GI (Harris et al., 2007; Harris, Yates,
et al. 2004). These apparent discrepant findings may point to
the heterogeneityof gyrification or to the heterogeneity in the
populations and the methodologies utilized to study GI.
Several approaches have studied whether abnormal surface
folding is an endophenotypic marker (Gottesman & Gould,
2003) for schizophrenia (Falkai et al., 2007; Vogeley et al.,
2001). Evidence from studies of unaffected siblings and indi-
viduals at risk for developing schizophrenia support gyrifica-
tion abnormalities a s being more severe in individuals who
go on to develop the illness (Harris, Whalley, et al., 2004; Vo-
ification, which may surface early in cortical development
(Armstrong et al., 1995), are trait markers of the illness, which
crease in the right frontal gyrification in individuals at a high
tive for developing schizophrenia (Harris et al., 2007; Harris,
Whalley, et al., 2004; Stanfield et al., 2007).
Several studies have deviated from the traditional GI ap-
3-D GI measures of cortical surface complexity (Cachia et al.,
2008; White, Andreasen, Nopoulos, & Magnotta, 2003; Wie-
2005) and the other using a comparison of surface area to vol-
ume, corrected to the two-thirds power (White et al., 2002).
However, surface area measures are highly variable and pa-
tient–control differences may be more difficult to assess. Using
a 3-D adaptation of the GI, Cachia et al. (2008) found that pa-
tients with chronic schizophrenia had lower sulcal complexity
that wasmorepronouncedinthetemporal and leftfrontal lobes.
Direct comparisons between the methodologies that uti-
lized surface curvature and those that implemented the GI
are difficult, as the GI does not differentiate between gyral
and sulcal regions. Thus, it is possible that sulcal widening
may be cancelled by gyral or global brain changes (Kulynych
et al., 1997).This is highlighted in children and adolescents
with schizophrenia showing opposing changes in gyral and
sulcal curvature in the frontal and temporal brain regions
(White et al., 2003). These findings have been replicated
and have been shown to be more pronounced in a younger
sample of children and adolescent with schizophrenia (R. K.
Lenroot, personal communication, 2006). In this sample, the
sulci developed less curvature (i.e., became broader) but the
gyri became more peaked, demonstrating an increased curva-
ture (Figure 3). This alteration in morphology results in in-
creased sulcal width, which has also been reported in ado-
lescents and adults with schizophrenia (Allmann, 2000;
Andreasen et al., 1994; Giedd et al., 1999; Pfefferbaum et al.,
1988; Weinberger, Torrey, Neophytides, & Wyatt, 1979).
Neural Connectivity in Schizophrenia
New approaches and insights from the field of complex net-
work studies (Strogatz, 2001) are currently entering systems
neuroscience.Applied tothe global organization of neural net-
works, such approaches have revealed high modularity, com-
Gyrification and connectivity
Table 1. Studies examining gyrification in schizophrenia spectrum disorders
Citation No. of SubjectsAge Years (SD) Sex M/F Methodol. and Brain RegionFindings
Kulynych et al. (1997) 9 Schiz
GI on MRI (whole brain)Mean GI values were significantly lower in
the left hemisphere in patients. Neither the
measures of age nor length of illness were
found to be significant predictors of GI.
Male patients had increased GI on the right
prefrontal cortex. No GI differences in
female patients and controls
Vogeley et al. (2000)24 SchizM: 51.3 (5.4)
F: 55.8 (8.9)
M: 54.2 (9.1)
F: 52.2 (13.6)
11/13 GI calculated on postmortem
brains (prefrontal cortex)
Narr et al. (2001) 25 Schiz
Cortical complexity of MRI
surface (whole brain)
Asymmetries of the gyri in the
temporoparietal regions in both males and
females with schizophrenia
The right GI was significantly higher in
siblings with schizophrenia or
schizoaffective disorder than in unaffected
Adolescents with schizophrenia had
significantly more broad or flattened
curvature in the sulci and more steeped or
peaked curvature in the gyri.
Patients with schizophrenia had a lower GI.
Patients with greater disorganized and
negative symptoms had a lower GI.
Paranoid subtype showed reduced cortical
folding restricted to the left hemisphere.
No differences in GI between patients with
schizophrenia and controls
Vogeley et al. (2001) 12 Schiz
GI on MRI (three slices in the
White et al. (2003)42 EOS
Curvature-based measures on
MRI (whole brain)
Sallet et al. (2003)40 Schiz
GI on MRI (whole brain)
Highley et al. (2003)61 Schiz M: 30.9 (7.7)
F: 33.4 (10.6)
M: 30.5 (8.6)
F: 40.3 (16.2)
40/21GI on MRI (whole brain)
Narr et al. (2004)50 FES
Cortical complexity of MRI
surface (whole brain)
First-episode male patients had increased
cortical folding in the right superior frontal
cortex, which was not seen in female
GI was significantly increased in the right
temporal lobe of the schizophrenic patients.
Harris, Whalley, et al.
GI on MRI (whole brain)
Harris, Yates, et al.
GI on MRI (whole brain) Right prefrontal lobe GI values were
significantly increased in individuals who
subsequently developed schizophrenia.
The left GI was lower in patients with no
differences in the right GI.
Adolescents above the defined schizotypy
cutoff scale had a significantly higher right
prefrontal lobe GI compared to those below
High-risk individuals who subsequently
developed schizophrenia had an increased
GI in the right prefrontal cortex.
Patients with schizophrenia had a lower GI in
the prefrontal cortex compared to controls,
but a higher prefrontal cortex GI compared
to children with mentally retarded
Patients with schizophrenia had a significant
lower GI in the rostral posterior cingulate,
and there were trend reductions in the
medial and caudal posterior cingulate.
Patients had a higher frontal but not a parieto-
occipital GI. There was no difference
between affected and unaffected family
members. A higher GI was found in
affected family members with greater
Patients had a lower global sulcal index in
both hemispheres. The global GI was lower
in the superior temporal sulcus, left middle
frontal sulcus, and Broca’s area.
Patients with schizophrenia and bipolar
disorder both had reduced gyrification
affecting both the ventral and dorsal
prefrontal regions. These reductions in the
GI were associated with cognitive
Jou, Hardan, &
Stanfield et al. (2007)
GI on MRI (single slice
anterior to corpus callosum)
GI on MRI (prefrontal cortex)
Harris et al. (2007)17 HR-C
GI on MRI (prefrontal cortex)
Bonnici et al. (2007) 25 Schiz
23 Schiz + MR
GI on MRI (prefrontal cortex)
Wheeler & Harper
Postmortem GI (posterior
Falkai et al. (2007)48 Schiz
29 Relatives +
53 Relatives –
GI on MRI (three slices in the
frontal lobe and three slices
at the parieto-occipital
44.8 (16.8) 29/24
Cachia et al. (2008)MRI based 3-D adaptation of
GI (whole brain)
McIntosh et al. (2009)28 Schiz
GI on MRI (prefrontal cortex)
Note: M, male; F, female; Schiz, chronic schizophrenia; GI, gyrification index; MRI, magnetic resonance imaging; NR, not reported; EOS, early-onset schizophrenia (children and adolescents with schizophrenia;
– is below threshold/low score); MR, mental retardation; Dx, diagnosis; BPD, bipolar disorder.
plexity, and efficiencyof the different types of anatomical and
functional neural connectivity (Sporns et al., 2004). Efficient
connectivity, for instance, can be assessed by the average
length of all shortest paths (ASP) across a network, where the
shortest paths represent the smallest number of edges required
to link two nodes. The ASP can be taken as an estimate for the
minimal number of processing steps in a neural system, and it
appears that neural networks are organized to maintain very
short ASP (Kaiser & Hilgetag, 2006). Conversely, network al-
network efficiency and functional impairments (see Figure 1;
Liu et al., 2008; Micheloyannis et al., 2006).
Network anomalies in schizophrenia can be identified in
measures of functional of as well as structural connectivity
(Karlsgodt, Sun, et al., 2008); however, a large number of re-
cent studies have focused on white-matter integrity and struc-
tural connectivityas indicated by the noninvasive approach of
DTI. These studies demonstrated mostly reductions of indica-
particular for frontal and temporal white matter (Kyriakopou-
los, Bargiotas, Barker, & Frangou, 2008; White, Nelson, &
mayresultfromweakerconnections,perhapsalso due theloss
of oligodendroglia (Konrad & Winterer, 2008), or through the
set of the disease (Begre & Koenig, 2008). Nonetheless, there
are also occasional reports of increases in functional (resting
state) connectivity in schizophrenia, for instance, in paranoid
schizophrenic subjects (Broyd et al., 2009).
structural connection systems, such asthe uncinate fasciculus, a
fiber tract connecting the temporal pole near the amygdala and
the orbitofrontal/ventrolateral prefrontal cortex, or connections
ened connections can be associated with specific functional as-
pects of schizophrenia. For example, the estimated strength of
the left superior longitudinal fasciculus, which is decreased in
working memory task (Karlsgodt, van Erp, et al., 2008). How-
ever, the exact relationship between variations in projection sys-
nia is currently still unclear for two reasons. First, the results of
the DTI investigations are themselves not consistent (Kyriako-
varied across studies, and several studies investigating the same
schizophrenic patients compared to healthy subjects (Kanaan
may be contradicted by corresponding studies of postmortem
ond, changes of structural connectivityas well as gyrification in
schizophrenia appear to be predominantly associated with the
manifest as weakened projections, schizophrenia may go along
with reduced as well as increased gyrification of the frontal
gray matter (cf. Table 2). These issues still need to be investi-
gated more systematically. For example, structural MR studies
lobes does not decrease over the life span in schizophrenic pa-
tients as it does in healthy subjects (Bartzokis et al., 2003).
Gyrification and brain efficiency
The phylogenyof the human nervous system has resulted in a
highly complex brain with a high degree of cortical folding.
Figure 3. Children and adolescents with schizophrenia demonstrate differ-
ences in gyrification that include (a) a widening of the sulci and a more
peaked appearance of gyri compared to (b) controls. These measures can
be quantified regionally following the identification of (c) whole brain sulci
and gyri. Adapted from “Gyrification Abnormalities in Childhood- and Ado-
lescent-Onset Schizophrenia,” by T. White, N. C. Andreasen, P. Nopoulos,
and V. Magnotta, 2003, Biological Psychiatry, 54, 418–426. Copyright
2003 by Elsevier. Adapted with permission. [A color version of this figure
can be viewed online at journals.cambridge.org/dpp]
T. White and C. C. Hilgetag
Humans, dolphins, and porpoises stand apart from other spe-
cies in having a disproportionately large cerebral cortex to
body size ratio (Allmann, 2000). The cortical folding in-
creases the surface area of the cortical gray matter and en-
hances the compactness of the brain.
creasing the cortical thickness, the development of gyral and
sulcal folds allows foran optimized compaction of neuronal fi-
bers. For example, a slightly larger lisencephalic or smoothed
This increase in cortical thickness would preserve the total vol-
ume of cortical gray matter; however, computational models
have shown that the necessary packing of connections within
the cortex would preclude such an evolutionary change (Murre
& Sturdy, 1995; Ruppin, Schwartz, & Yeshurun, 1993). Be-
cause each neuron has more than a thousand connections with
would be highly inefficient neuronal pathways,with someneu-
ronstaking circuitous paths in order to reach their final destina-
tion (Chklovskii, Schikorski, & Stevens, 2002).
may account for the increase in surface area far exceeding the
growth in cortical thickness (Welker, 1990). The surface area
of the human brain is 1,700 times greater than in shrews, yet
the thickness of the cortex is only 6 times greater (Hofman,
1989). Furthermore, the surface area of the human brain is
on average 10 times larger than that of the macaque monkey,
yet only 2 times as thick (Rakic, 1995). Thus, the cortex ex-
resulting in a convoluted human cortical sheet that is about 3
bas, 2005, 2006; Richman et al., 1975; Toro & Burnod, 2005;
VanEssen,1997; Welker,1990).Theparcellation ofbraintis-
sue into the computationally powerful cortical layers and effi-
cient signal transmission through myelinated fibers, coupled
with acompacted gyrification pattern, have resulted in an effi-
cient wiring and volume arrangement for the very dense con-
nectivity (Murre & Sturdy, 1995; Ruppin et al., 1993; Wen &
whetheralterations in function alsoresult in alterations of form,
mediated by neural connectivity. There is a direct relationship
between disorders of neuronal migration (i.e., lissencephaly)
and aberrant neuronal connectivity (Stewart, Richman,& Cavi-
ness, 1975). These disorders of neuronal migration have pro-
found effects on the gyral and sulcal patterns in the brain and
are associated with significant cognitive deficits. The timing
of the pathology for these developmental disorders occurs be-
fore 24 weeks gestational age, a time when neuronal migration
is laying the foundation for gyrification (Neal et al., 2007).
Gyrification in schizophrenia
There is an emerging literature describing differences in the
brain surface morphology in patients with schizophrenia (Ta-
ble 1). Studies in first episode and chronic schizophrenia in
adults have primarily utilized the GI technique, which has an
intrinsic property of controlling for differences in brain size.
ification and is unable to differentiate the subtle changes that
may occur separately within the sulci and gyri. Differences
in methodologies applied and populations studied may ac-
count for some of the discrepancies in the literature to date.
There does appear to be some convergence, however, toward
who are early in the course of their illness (Table 2).
Differences in patient demographics and clinical variables
(i.e., duration and type of medication use) between studies
present in male patients (Narr et al., 2004; Vogeley et al.,
2000). In addition, conflicting findings reported by the same
site using similar approaches to measure GI (Bonnici et al.,
2007; Harris et al., 2007; Harris, Whalley, et al., 2004; Harris,
also support differences in demographics or clinical variables
Table 2. Consolidated results of gyrification studies of schizophrenia and individuals at high risk
Brain RegionIncreased GI Decreased GIAltered Surface Morphology
Whole brain Kulynych et al. (1997), Sallet
et al. (2003)
Bonnici et al. (2007), Jou
et al. (2005), McIntosh
et al. (2009)
Cachia et al. (2008),
White et al. (2003)
Cachia et al. (2008), Narr et al.
(2001), White et al. (2003)
Frontal lobe Falkai et al. (2007), Harris et al. (2007), Harris,
Whalley, et al. (2004), Narr et al. (2004),
Stanfield et al. (2008),Vogeleyet al. (2000,2001)
Harris, Yates, et al. (2004)Temporal lobe Cachia et al. (2008), Narr et al.
(2001), White et al. (2003)
Narr et al. (2001) Parietal lobe
Wheeler & Harper (2007)
Narr et al. (2004), Vogeley et al. (2000)Narr et al. (2001)
Note: GI, gyrification index. No change in the GI was noted by Highley et al. (2003).
Gyrification and connectivity
2007; Harris, Whalley, et al., 2004) and first-episode (Harris,
Yates, et al., 2004) patients may be more likely to have in-
creased GI, whereas chronic patients may have resultant
sures (Bonnici et al., 2007; McIntosh et al., 2009).
Another possible explanation for discrepant findings be-
tween the studies is the differences in image processing ap-
mensional approaches may be more prone to anatomic
variability (White et al., 2010). For example, measures of GI
of the slices (Zilles et al., 1997). However, this variability is
likely significantly reduced by acquiring coronal sections
and averaging over multiple slices, which is commonly done
(Moorhead et al., 2006). As an alternative to the standard 2-
D approaches, 3-D approaches are not dependent on slice or-
ientation and thus will likely provide more accurate measures
of overall brain complexity (Schaer et al., 2008; White et al.,
2010). Studies utilizing 3-D approaches have also shown dis-
crepant findings, showing increases in cortical complexity
(Narret al., 2004) and decreases in gyrification in schizophre-
Rakic & Rakic, 1984) and decreased gyrification (Van Essen,
patterns of the brain.
ample, there is considerable heterogeneity in the location of
white matter differences in DTI studies in schizophrenia (Kyr-
iakopoulos et al., 2008; White et al., 2008). Furthermore, most
tion that patients with schizophrenia have white matter deficits
that are spatially homogeneous (White, Schmidt, & Karatekin,
2009). For example, voxel-based approaches imply that white
matter regions will spatially overlap when brains are coregis-
tered into the same anatomical space; however, this may not
terns of abnormalities between white matter and gyrification.
schizophrenia have consistently shown a decrease in the vol-
ume of cortical gray matter and a resultant increase in the sur-
face cerebrospinal fluid (Friedman et al., 1999; Giedd et al.,
1999; Kumra et al., 2000; Rapoport et al., 1999; Sowell,
et al., 2001). Given these changes, it would be reasonable to
expect that surface patterns show developmental changes in
conjunction with the gray matter loss. However, as described
above, postmortem studies of human brain gyrification appear
tosupport aconstant GI frombirthtolate adulthood innormal
brains (Armstrong et al., 1995; Zilles et al., 1988). This would
Huttenlocher, 1979, 1990; Huttenlocher & Dabholkar, 1997;
ovlev & Lecours, 1967) alter the cortical gray matter in such a
manner so as not to affect the GI. However, MRI measures of
the GI have shown age-related differences in healthy subjects
ancies between these modalities.
Although the primary disorders of neuronal migration pre-
sent early in life and cannot be directly compared to indi-
viduals with schizophrenia, they do provide evidence for a
link between neuronal connectivity and changes in brain sur-
face morphology. In addition, there is a temporal relationship
between neuronal migration and patterns of gyrification, with
disorders that affect migration early having more pronounced
alterations in the pattern of gyrification. As an archeologist
piecestogetherclues about past events based on current infor-
velopmental aberrations based on the present gyrification pat-
gyrification suggest that the GI remains relatively stable fol-
lowing birth (Armstrong et al., 1995) and gyrification mea-
tors (Gregorio et al., 2009), patient–control differences may
et al., 1997). However, MRI studies of gyrification have now
found a stable GI following birth (Bonnici et al., 2007; Mag-
mortem studies with larger numbers of subjects are necessary
to confirm the stability in age-related trajectory of GI.
The pattern of gyrification abnormalities in children and
adolescents with schizophrenia reflects a combination of cor-
tical thinning and alterations in gyral and sulcal curvature
(White et al., 2003). Studies with increased gyrification also
are associated with increased cortical thickness (Thompson
et al., 2005), supporting an inverse relationship between the
thickness of the cortex and gyrification measures. The sulci
demonstrated more pronounced differences in schizophrenia,
showing both a decrease in cortical thickness and a flattening
of the convexity. In addition, the gyri developed greater con-
cavity, although was also associated with greater gray matter
thinning. Because the histology of cortical gyri and sulci
shows differences in measures of global orientation (Welker,
1990), it was postulated that these changes were consistent
with aberrantpruning underthetension-based morphogenesis
hypothesis of gyrification (Van Essen, 1997).
Neural connectivity in schizophrenia
connectivity in schizophrenic subjects, for the whole brain as
well as for specific regional connection systems. Although
to gyrification (Hilgetag & Barbas, 2006), likely via the shap-
lation between specific projection systems and characteristic
cortical landmarks is still unclear. A better understanding
T. White and C. C. Hilgetag
sulci tend to orient horizontal to the cortical surface, due par-
tially to fibers that traverse the sulci (Welker, 1990). Thus,
fibers, might create a broadening of the sulci. Moreover, the
neurons within the gyri tend to be more numerous and run on
bas, 2005, 2006; Richman et al., 1975; Toro & Burnod, 2005;
Van Essen, 1997;Welker,1990).Releasingtensioninthese fi-
come more peaked. Finally, the sulcal and gyral brain regions
that showed the greatest differences in surface morphology
also had the most pronounced decreases in cortical thickness
(White et al., 2003), lending additional support to the link be-
tween neuronal connectivity and gyrification.
Toward improved models of gyrification in schizophrenia
In summary, there is emerging evidence for alterations in the
gyrification of the brain in those who develop schizophrenia.
later develop schizophrenia demonstrate greater gyrification
abnormalities than those high-risk individuals who do not
progress to the illness (Harris et al., 2007; Harris, Whalley,
et al., 2004). However, several discordant findings in the lit-
erature render the relationship between gyrification, brain
connectivity, and schizophrenia still uncertain and a number
tivityasobservedinschizophrenia result inless ormoreover-
all cortical folding? Are there perhaps differences between
the local and global impact of pathologically altered connec-
tivity on gyrification? How exactly are connectivity and gyr-
ification linked to other structural measures, such as the
amount of white and gray matter? Specifically, because there
appears to be an inverse relationship between sulcal cortical
thickness and gyrification (Thompson et al., 2005; White
et al., 2003), it is important to determine the underlying neu-
robiologic mechanisms associated with this relationship.
How does the developmental trajectory of gyrification differ
between those who do and do not develop schizophrenia? Fi-
nally, do the different measures of GI remain constant over
the life span, or do specific changestake place in morphology
of the sulci and gyri over time. If age-related changes do oc-
cur, are different methodologies utilized to study gyrification
more sensitive to different aspects of these changes.
There are a number of different directions for researchers to
address these important questions. The field is still lacking
a methodological study that evaluates the different quantita-
tive techniques to measure gyrification. Optimally, this study
would couple high-resolution postmortem and MRI tech-
niques to evaluate differences in techniques and identify a
gold standard. Ideally, this will also allow for an evaluation
of the relationship between form (surface morphology) and
function (connectivity) of the brain. Finally, longitudinal
studies will be able to assess changes over time for the differ-
ent measures of gyrification.
Addington, J., Addington, D., & Maticka-Tyndale, E. (1991). Cognitive
functioning and positive and negative symptoms in schizophrenia.
Schizophrenia Research, 5, 123–134.
Agartz,I.,Andersson,J. L.,& Skare, S.(2001).Abnormal brainwhite matter
in schizophrenia: A diffusion tensor imaging study. NeuroReport, 12,
Allmann, J. (2000). Evolving brains. New York: W. H. Freeman & Co.
Andreasen, N. C., Flashman, L., Flaum, M., Arndt, S., Swayze V, III,
O’Leary, D. S., et al. (1994). Regional brain abnormalities in schizophre-
nia measured withmagneticresonanceimaging. Journalof the American
Medical Association, 272, 1763–1769.
Flaum, M. (1999). Defining the phenotype of schizophrenia: Cognitive
dysmetria and its neural mechanisms. Biological Psychiatry, 46, 908–
Andreasen, N. C., & Olsen, S. (1982). Negative v positive schizophrenia.
Definition and validation. Archives of General Psychiatry, 39, 789–794.
Andreasen, N. C., Paradiso, S., & O’Leary, D. S. (1998). “Cognitive dys-
metria” as an integrative theory of schizophrenia: A dysfunction in corti-
cal–subcortical–cerebellar circuitry? Schizophrenia Bulletin, 24, 203–
Ardekani, B. A., Nierenberg, J., Hoptman, M. J., Javitt, D. C., & Lim, K. O.
(2003). MRI studyof white matter diffusion anisotropy in schizophrenia.
NeuroReport, 14, 2025–2029.
Armstrong, E., Curtis, M., Buxhoeveden, D. P., Fregoe, C., Zilles, K.,
A test of the mechanical folding hypothesis. Cerebral Cortex, 1, 426–
Armstrong, E., Schleicher, A., Omran, H., Curtis, M., & Zilles, K. (1995).
The ontogeny of human gyrification. Cerebral Cortex, 5, 56–63.
J. (2003). Dysregulated brain development in adult men with schizophre-
nia: A magnetic resonance imaging study. Biological Psychiatry, 53,
Begre, S., & Koenig, T. (2008). Cerebral disconnectivity: An early event in
schizophrenia. Neuroscientist, 14, 19–45.
Benes, F. M. (1989). Myelination of cortical–hippocampal relays during late
adolescence. Schizophrenia Bulletin, 15, 585–593.
Benes, F. M. (1998). Brain development:VII. Human brain growth spansde-
cades. American Journal of Psychiatry, 155, 1489.
Bonnici, H. M., William, T., Moorhead, J., Stanfield, A. C., Harris, J. M.,
Owens, D. G., et al. (2007). Pre-frontal lobe gyrification index in schizo-
phrenia, mental retardation and comorbid groups: An automated study.
NeuroImage, 35, 648–654.
Braitenberg, V., & Schu ¨z, A. (1998). Cortex: Statistics and geometry of neu-
ronal connectivity. Berlin: Springer.
Barke,E.J.(2009). Default-modebrain dysfunctionin mentaldisorders: A
Buchsbaum, M. S., Tang, C. Y., Peled, S., Gudbjartsson, H., Lu, D., Hazlett,
bolic rate in schizophrenia. NeuroReport, 9, 425–430.
Burns, J., Job, D., Bastin, M. E., Whalley, H., Macgillivray, T., Johnstone, E.
C., et al. (2003). Structural disconnectivity in schizophrenia: A diffusion
tensor magnetic resonance imaging study. British Journal of Psychiatry,
Cachia, A., Paillere-Martinot, M. L., Galinowski, A., Januel, D., de Beaure-
paire, R., Bellivier, F., et al. (2008). Cortical folding abnormalities in
schizophrenia patients with resistant auditory hallucinations. Neuro-
Image, 39, 927–935.
Gyrification and connectivity
Changizi, M. A. (2001). Principles underlying mammalian neocortical scal-
ing. Biological Cybernetics, 84, 207–215.
Chenn, A., & Walsh, C. A. (2002). Regulation of cerebral cortical size by
control of cell cycle exit in neural precursors. Science, 297, 365–369.
Chklovskii, D. B., Schikorski, T., & Stevens, C. F. (2002). Wiring optimiza-
tion in cortical circuits. Neuron, 34, 341–347.
Colter, N., Battal, S., Crow, T. J., Johnstone, E. C., Brown, R., & Bruton, C.
(1987). White matter reduction in the parahippocampal gyrus of patients
with schizophrenia. Archives of General Psychiatry, 44, 1023.
Davis, K. L., Stewart, D. G., Friedman, J. I., Buchsbaum, M., Harvey, P. D.,
for myelin-related dysfunction. Archives of General Psychiatry, 60, 443–
Falkai, P., Honer, W. G., Kamer, T., Dustert, S., Vogeley, K., Schneider-Ax-
mann, T., et al. (2007). Disturbed frontal gyrification within families
affected with schizophrenia. Journal of Psychiatric Research, 41, 805–
Franze, K., Reichenbach, A., & Ka ¨s, J. (2008). Biomechanics of the CNS. In
A. Kamkin & I. Kiseleva (Eds.), Mechanosensitivity in cells and tissues.
Mechanosensitivity of the nervous system (pp. 173–213). Dordrecht:
Friedman, L., Findling, R. L., Kenny, J. T., Swales, T. P., Stuve, T. A., Jes-
berger, J. A., et al. (1999). An MRI study of adolescent patients with ei-
jects. Biological Psychiatry, 46, 78–88, Erratum, 584.
Friston, K. J. (1994). Functional and effective connectivity in neuroimaging:
A synthesis. Human Brain Mapping, 2, 56–78.
Giedd, J. N., Jeffries, N. O., Blumenthal, J., Castellanos, F. X., Vaituzis, A.
C., Fernandez, T., et al. (1999). Childhood-onset schizophrenia: Progres-
sive brain changes during adolescence. Biological Psychiatry, 46, 892–
Goldman-Rakic, P. S. (1980). Morphological consequences of prenatal in-
jury to the primate brain. Progress in Brain Research, 53, 1–19.
Goldman-Rakic, P. S., & Rakic, P. (1984). Experimental modification of
gyral patterns. In N. Geschwind & A. Galaburda (Eds.), Cerebral domi-
nance (pp. 179–192). Cambridge, MA: Harvard University Press.
Gottesman, I. I., & Gould, T. D. (2003). The endophenotype concept in psy-
chiatry: Etymology and strategic intentions. American Journal of Psy-
chiatry, 160, 636–645.
Gregorio, S. P., Sallet, P. C., Do, K. A., Lin, E., Gattaz, W. F., & Dias-Neto,
E. (2009). Polymorphisms in genes involved in neurodevelopment may
be associated with altered brain morphology in schizophrenia: Prelimi-
nary evidence. Psychiatry Research, 165, 1–9.
Greicius, M. D., Supekar, K., Menon, V., & Dougherty, R. F. (2009). Rest-
ing-state functional connectivity reflectsstructural connectivity in the de-
fault mode network. Cerebral Cortex, 19, 72–78.
Hakak, Y., Walker, J. R., Li, C., Wong, W. H., Davis, K. L., Buxbaum, J. D.,
et al. (2001). Genome-wide expression analysis reveals dysregulation of
myelination-related genes in chronic schizophrenia. Proceedings of the
National Academy of Sciences of the United States of America, 98,
Harris, J. M., Moorhead, T. W., Miller, P., McIntosh, A. M., Bonnici, H. M.,
Owens, D. G., et al. (2007). Increased prefrontal gyrification in a large
high-risk cohort characterizes those who develop schizophrenia and re-
flects abnormal prefrontal development. Biological Psychiatry, 62,
M. (2004). Abnormal cortical folding in high-risk individuals: A
predictor of the development of schizophrenia? Biological Psychiatry,
Harris, J. M., Yates, S., Miller, P., Best, J. J., Johnstone, E. C., & Lawrie, S.
M. (2004). Gyrification in first-episode schizophrenia: A morphometric
study. Biological Psychiatry, 55, 141–147.
Heckers, S., Heinsen, H., Geiger, B., & Beckmann, H. (1991). Hippocampal
neuron number in schizophrenia. A stereological study. Archives of Gen-
eral Psychiatry, 48, 1002–1008.
of axonal development. Cell Biochemistry and Biophysics, 27, 135–155.
Highley, J. R., DeLisi, L. E., Roberts, N., Webb, J. A., Relja, M., Razi, K.,
et al. (2003). Sex-dependent effects of schizophrenia: An MRI study of
Highley, J. R., Walker, M. A., Esiri, M. M., Crow, T. J., & Harrison, P. J.
(2002). Asymmetry of the uncinate fasciculus: A post-mortem study of
normal subjects and patients with schizophrenia. Cerebral Cortex, 12,
Hilgetag, C. C., & Barbas, H. (2005). Developmental mechanics of the pri-
mate cerebral cortex. Anatomy and Embryology (Berlin), 210, 411–417.
Hilgetag, C. C., & Barbas, H. (2006). Role of mechanical factors in the mor-
phology of the primate cerebral cortex. PLoS Computational Biology,
His, W. (1874). Unsere Ko ¨rperform und das physiologische Problem ihrer
Entstehung. Leipzig: F. C. W. Vogel.
Hofman, M. A. (1989). On the evolution and geometry of the brain in mam-
mals. Progress in Neurobiology, 32, 137–158.
Huttenlocher, P. R. (1979). Synaptic density in human frontal cortex—De-
velopmental changes and effects of aging. Brain Research, 163, 195–
velopment. Neuropsychologia, 28, 517–527.
Huttenlocher, P. R., & Dabholkar, A. S. (1997). Regional differences in syn-
aptogenesis in human cerebral cortex. Journal of Comparative Neurol-
ogy, 387, 167–178.
Huttenlocher, P. R., De Courten, C., Garey, L. J., & van der Loos, H. (1982).
Synapticdevelopmentin humancerebral cortex.International Journalof
Neurology, 17, 144–154.
Johnstone, E. C., Owens, D. G., Frith, C. D., & Crow, T. J. (1987). The rel-
ative stability of positive and negative features in chronic schizophrenia.
British Journal of Psychiatry, 150, 60–64.
Jou, R. J., Hardan, A. Y., & Keshavan, M. S. (2005). Reduced cortical fold-
ing in individuals at high risk for schizophrenia: A pilot study. Schizo-
phrenia Research, 75, 309–313.
Kaiser,M.,& Hilgetag,C.C.(2006).Nonoptimal componentplacement,but
PLoS Computational Biology, 2(7), e95.
McGuire, P. K. (2005). Diffusion tensor imaging in schizophrenia. Bio-
logical Psychiatry, 58, 921–929.
Karlsgodt, K. H., Sun, D., Jimenez, A. M., Lutkenhoff, E. S., Willhite, R.,
pathology, 20, 1297–1327.
Karlsgodt, K. H., van Erp, T. G., Poldrack, R. A., Bearden, C. E., Nuechter-
lein, K. H., & Cannon, T. D. (2008). Diffusion tensor imaging of the su-
perior longitudinal fasciculus and working memory in recent-onset
schizophrenia. Biological Psychiatry, 63, 512–518.
Kendi, M., Kendi, A. T., Lehericy, S., Ducros, M., Lim, K. O., Ugurbil, K.,
et al. (2008). Structural and diffusion tensor imaging of the fornix in
childhood- and adolescent-onset schizophrenia. Journal of the American
Academy of Child & Adolescent Psychiatry, 47, 826–832.
Ko ¨bbert, C., Apps, R., Bechmann, I., Lanciego, J. L., Mey, J., & Thanos, S.
(2000). Current concepts in neuroanatomical tracing. Progress in Neuro-
biology, 62, 327–351.
Koenderink, J. J., & van Doorn, A. J. (1992). Surface shape and curvature
scales. Image and Vision Computing, 10, 557–564.
Konrad, A., & Winterer, G. (2008). Disturbed structural connectivity in
schizophrenia primary factor in pathology or epiphenomenon? Schizo-
phrenia Bulletin, 34, 72–92.
stem and progenitor cell division may underlie evolutionary cortical ex-
pansion. Nature Reviews Neuroscience, 7, 883–890.
Kubicki, M., McCarley, R., Westin, C. F., Park, H. J., Maier, S., Kikinis, R.,
et al. (2007). A review of diffusion tensor imaging studies in schizophre-
nia. Journal of Psychiatric Research, 41, 15–30.
Kulynych, J. J., Luevano, L. F., Jones, D. W., & Weinberger, D. R. (1997).
Cortical abnormality in schizophrenia: An in vivo application of the gyr-
ification index. Biological Psychiatry, 41, 995–999.
A voxel-based diffusion tensor imaging study. Journal of the American
Academy of Child & Adolescent Psychiatry, 44, 934–941.
Kumra, S., Ashtari, M., McMeniman, M., Vogel, J., Augustin, R., Becker, D.
E., et al. (2004). Reduced frontal white matter integrity in early-onset
Kumra, S., Giedd,J. N.,Vaituzis,A. C., Jacobsen, L. K.,McKenna, K.,Bed-
well, J., et al. (2000). Childhood-onset psychotic disorders: Magnetic
T. White and C. C. Hilgetag
resonanceimaging of volumetric differences in brain structure. American
Journal of Psychiatry, 157, 1467–1474.
Kyriakopoulos, M., Bargiotas, T., Barker, G. J., & Frangou, S. (2008). Diffu-
sion tensor imaging in schizophrenia. European Psychiatry, 23, 255–273.
Lawrie, S. M., Buechel, C., Whalley, H. C., Frith, C. D., Friston, K. J., &
Johnstone, E. C. (2002).Reduced frontotemporal functionalconnectivity
in schizophrenia associated with auditory hallucinations. Biological Psy-
chiatry, 51, 1008–1011.
LeGrossClark,W. E.(1945).Deformationpatterns onthecerebral cortex.In
(pp. 1–23). Oxford: Oxford University Press.
Lim, K. O., Hedehus, M., Moseley, M., de Crespigny, A., Sullivan, E. V., &
Pfefferbaum, A. (1999). Compromised white matter tract integrity in
schizophrenia inferred from diffusion tensor imaging. Archives of Gen-
eral Psychiatry, 56, 367–374.
Liu, Y., Liang, M., Zhou, Y., He, Y., Hao, Y., Song, M., et al. (2008). Dis-
rupted small-world networks in schizophrenia. Brain, 131, 945–961.
Luders, E., Narr, K. L., Thompson, P. M., Rex, D. E., Jancke, L., Steinmetz,
H., et al. (2004). Gender differences in cortical complexity. Nature Neu-
roscience, 7, 799–800.
Luders, E., Thompson, P. M., Narr, K. L., Toga, A. W., Jancke, L., & Gaser,
C. (2006). A curvature-based approach to estimate local gyrification on
the cortical surface. NeuroImage, 29, 1224–1230.
Magnotta, V. A., Andreasen, N. C., Schultz, S. K., Harris, G., Cizadlo, T.,
Heckel, D., et al. (1999). Quantitative in vivo measurement of gyrifica-
tion in the human brain: changes associated with aging. Cerebral Cortex,
McIntosh, A. M., Moorhead, T. W., McKirdy, J., Hall, J., Sussmann, J. E.,
Stanfield, A. C., et al. (2009). Prefrontal gyral folding and its cognitive
correlates in bipolar disorderand schizophrenia. Acta Psychiatrica Scan-
dinavica, 119, 192–198.
Meyer-Lindenberg, A., Poline, J. B., Kohn, P. D., Holt, J. L., Egan, M. F.,
Weinberger, D. R., et al. (2001). Evidence for abnormal cortical func-
tional connectivity during working memory in schizophrenia. American
Journal of Psychiatry, 158, 1809–1817.
Meyer-Lindenberg, A. S., Olsen, R. K., Kohn, P. D., Brown, T., Egan, M. F.,
Weinberger, D. R., et al. (2005). Regionally specific disturbance of dor-
solateral prefrontal-hippocampal functional connectivity in schizophre-
nia. Archives of General Psychiatry, 62, 379–386.
kas, M., et al. (2006). Small-world networks and disturbed functional
connectivity in schizophrenia. Schizophrenia Research, 87, 60–66.
Moorhead, T. W., Harris, J. M., Stanfield, A. C., Job, D. E., Best, J. J., John-
stone, E. C., et al. (2006). Automated computation of the gyrification in-
tation. NeuroImage, 31, 1560–1566.
Murre, J. M., & Sturdy, D. P. (1995). The connectivity of the brain: Multi-
level quantitative analysis. Biological Cybernetics, 73, 529–545.
Narr, K., Thompson, P., Sharma, T., Moussai, J., Zoumalan, C., Rayman, J.,
& Toga, A. (2001). Three-dimensional mapping of gyral shape and cor-
tical surface asymmetries in schizophrenia: Gender effects. American
Journal of Psychiatry, 158, 244–255.
Narr,K. L., Bilder, R. M., Kim,S., Thompson, P. M., Szeszko, P., Robinson,
D., et al. (2004). Abnormal gyral complexity in first-episode schizophre-
nia. Biological Psychiatry, 55, 859–867.
Neal, J., Takahashi, M., Silva, M., Tiao, G., Walsh, C. A., & Sheen, V. L.
(2007). Insights into the gyrification of developing ferret brain by mag-
netic resonance imaging. Journal of Anatomy, 210, 66–77.
Nopoulos, P., Flaum, M., O’Leary, D., & Andreasen, N. C. (2000). Sexual
position and surface anatomy using magnetic resonance imaging. Psy-
chiatry Research, 98, 1–13.
Pfefferbaum, A., Zipursky, R. B., Lim, K. O., Zatz, L. M., Stahl, S. M., &
Jernigan, T. L. (1988). Computed tomographic evidence for generalized
sulcal and ventricularenlargement in schizophrenia. Archives of General
Psychiatry, 45, 633–640.
Piao, X., Hill, R. S., Bodell, A., Chang, B. S., Basel-Vanagaite, L., Strauss-
berg, R., et al. (2004). G protein-coupled receptor-dependent develop-
ment of human frontal cortex. Science, 303(5666), 2033–2036.
Rakic,P. (1988).Specification of cerebral cortical areas. Science, 241(4862),
Rakic, P. (1995). A small step for the cell, a giant leap for mankind: A hy-
pothesis of neocortical expansion during evolution. Trends in Neu-
roscience, 18, 383–388.
nandez, T., et al. (1999). Progressive cortical change during adolescence
in childhood-onset schizophrenia. A longitudinal magnetic resonance
imaging study. Archives of General Psychiatry, 56, 649–654.
Richman, D. P., Stewart, R. M., Hutchinson, J. W., & Caviness, V. S., Jr.
(1975). Mechanical model of brain convolutional development. Science,
nah,D. E., et al.(2006). Evidenceof alteredprefrontal–thalamic circuitry
in schizophrenia: An optimized diffusion MRI study. NeuroImage, 32,
Ruppin, E., Schwartz, E. L., & Yeshurun, Y. (1993). Examining the volume
Biological Cybernetics, 70, 89–94.
Sallet, P. C., Elkis, H., Alves, T. M., Oliveira, J. R., Sassi, E., Campi de Cas-
tro, C., et al. (2003). Reduced cortical folding in schizophrenia: An MRI
morphometric study. American Journal of Psychiatry, 160, 1606–1613.
Schaer,M.,Cuadra,M.B.,Tamarit,L., Lazeyras,F.,Eliez,S.,&Thiran,J. P.
(2008). A surface-based approach to quantify local cortical gyrification.
IEEE Transactions in Medical Imaging, 27, 161–170.
Schlosser, R., Gesierich, T., Kaufmann, B., Vucurevic, G., Hunsche, S., Ga-
wehn, J., et al. (2003). Altered effective connectivity during working
memoryperformancein schizophrenia:A study withfMRI and structural
equation modeling. NeuroImage, 19, 751–763.
Sowell, E. R., Toga, A. W., & Asarnow, R. (2000). Brain abnormalities ob-
served in childhood-onset schizophrenia: A review of the structural mag-
netic resonance imaging literature. Mental Retardation and Develop-
mental Disabilities Research Reviews, 6, 180–185.
Sporn, A. L., Greenstein, D. K., Gogtay, N., Jeffries, N. O., Lenane, M.,
Gochman, P., et al. (2003). Progressive brain volume loss during adoles-
Sporns, O., Chialvo, D. R., Kaiser, M., & Hilgetag, C. C. (2004). Organiza-
tion, development and function of complex brain networks. Trends in
Cognitive Science, 8, 418–425.
Stanfield, A. C., Moorhead, T. W., Harris, J. M., Owens, D. G., Lawrie, S.
M., & Johnstone, E. C. (2008). Increased right prefrontal cortical folding
in adolescents at risk of schizophrenia for cognitive reasons. Biological
Psychiatry, 63, 80–85.
Stephan, K. E., Magnotta, V. A., White, T., Arndt, S., Flaum, M., O’Leary,
tivity in schizophrenia measured by fMRI during a simple motor task.
Psychological Medicine, 31, 1065–1078.
Stewart, R. M., Richman, D. P., & Caviness, V. S., Jr. (1975). Lissencephaly
and pachygyria: An architectonic and topographical analysis. Acta Neu-
ropathologica (Berlin), 31, 1–12.
Strogatz, S. H. (2001). Exploring complex networks. Nature, 410, 268–276.
Thompson, P. M., Cannon, T. D., Narr, K. L., van Erp, T., Poutanen, V. P.,
Huttunen, M., et al. (2001). Genetic influences on brain structure. Nature
Neuroscience, 4, 1253–1258.
Thompson, P. M., Lee, A. D., Dutton, R. A., Geaga, J. A., Hayashi, K. M.,
Eckert, M. A., et al. (2005). Abnormal cortical complexity and thickness
profiles mapped in Williams syndrome. Journal of Neuroscience, 25,
Thompson, P. M., Schwartz, C., Lin, R. T., Khan, A. A., & Toga, A. W.
(1996). Three-dimensional statistical analysis of sulcal variability in the
human brain. Journal of Neuroscience, 16, 4261–4274.
Thompson, P. M., Vidal, C., Giedd, J. N., Gochman, P., Blumenthal, J., Ni-
colson, R., et al. (2001). Mapping adolescent brain change reveals dy-
namic wave of accelerated gray matter loss in very early-onset schizo-
phrenia. Proceedings of the National Academy of Sciences of the
United States of America, 98, 11650–11655.
Toro, R., & Burnod,Y. (2005). A morphogenetic model for the development
of cortical convolutions. Cerebral Cortex, 15, 1900–1913.
pact wiring in the central nervous system. Nature, 385, 313–318.
Neuroscience, 8, 12.
Vogeley, K., Schneider-Axmann, T., Pfeiffer, U., Tepest, R., Bayer, T. A.,
Bogerts, B., et al. (2000). Disturbed gyrification of the prefrontal region
in male schizophrenic patients: A morphometric postmortem study.
American Journal of Psychiatry, 157, 34–39.
Gyrification and connectivity
Vogeley, K., Tepest, R., Pfeiffer, U., Schneider-Axmann, T., Maier, W.,
Honer, W. G., et al. (2001). Right frontal hypergyria differentiation in af-
fected and unaffected siblings from families multiply affected with
schizophrenia: A morphometric MRI study. American Journal of Psy-
chiatry, 158, 494–496.
H., et al. (1988). Brain interactions in chronic schizophrenics under rest-
ing and activation conditions. Schizophrenia Research, 1, 47–53.
Weinberger, D. R., Berman, K. F., Suddath, R., & Torrey, F. (1992). Evi-
dence of dysfunction of a prefrontal-limbic network in schizophrenia:
A magnetic resonance and regional cerebral blood flow study of discor-
dantmonozygotic twins. American Journalof Psychiatry, 149, 890–897.
Weinberger, D. R., Torrey, E. F., Neophytides, A. N., & Wyatt, R. J. (1979).
Structural abnormalities in the cerebral cortex of chronic schizophrenic
patients. Archives of General Psychiatry, 36, 935–939.
Welker, W. (1990). Why does cerebral cortex fissure and fold. In E. G. Jones
& A. Peters (Eds.), Cerebral cortex (pp. 3–136). New York: Plenum
Wen, Q., & Chklovskii, D. B. (2005). Segregation of the brain into gray and
white matter: A design minimizing conduction delays. PLoS Computa-
tional Biology, 1(7), e78.
Wheeler, D. G., & Harper, C. G. (2007). Localised reductions in gyrification
in the posterior cingulate: Schizophrenia and controls. Progress in Neu-
ropsychopharmacology and Biological Psychiatry, 31, 319–327.
White, T., Andreasen, N. C., & Nopoulos, P. (2002). Brain volumes and sur-
face morphology in monozygotic twins. Cerebral Cortex, 12, 486–493.
White, T., Andreasen, N. C., Nopoulos, P., & Magnotta, V. (2003). Gyrifica-
tion abnormalities in childhood- and adolescent-onset schizophrenia.
Biological Psychiatry, 54, 418–426.
ropsychological performance in first-episode adolescents with schizo-
phrenia: A comparison with first-episode adults and adolescent control
subjects. Biological Psychiatry, 60, 463–471.
White, T., Kendi, A. T., Lehericy, S., Kendi, M., Karatekin, C., Guimaraes,
A., et al. (2007). Disruption of hippocampal connectivity in children and
study. Schizophrenia Research, 90, 302–307.
White, T., Nelson, M., & Lim, K. O. (2008). Diffusion tensor imaging in
psychiatric disorders. Topics in Magnetic Resonance Imaging, 19, 97–
White, T., Schmidt, M., & Karatekin, C. (2009). White matter “potholes” in
early-onset schizophrenia: A new approach to evaluate white matter mi-
crostructure using diffusion tensor imaging. Psychiatry Research, 174,
White, T., Su, S., Schmidt, M., Kao, C. Y., & Sapiro, G. (2010). The devel-
opment of gyrification in childhood and adolescence. Brain and Cogni-
tion, 72, 36–45.
Wiegand, L. C., Warfield, S. K., Levitt, J. J., Hirayasu, Y., Salisbury, D. F.,
Heckers, S., et al. (2005). An in vivo MRI study of prefrontal cortical
complexity in first-episode psychosis. American Journal of Psychiatry,
(2003). Functional and effective frontotemporal connectivity and genetic
risk for schizophrenia. Biological Psychiatry, 54, 1181–1192.
Yakovlev, P. I., & Lecours, A. R. (1967). The myelogenetic cycles of re-
gional maturation of the brain. In A. Minkowski (Ed.),Regional develop-
ment of the brain in early life (pp. 3–70). Oxford: Blackwell.
Zilles, K., Armstrong, E., Schleicher, A., & Kretschmann, H. J. (1988). The
ology, 179, 173–179.
Zilles, K., Schleicher, A., Langemann, C., Amunts, K., Morosan, P., Palo-
mero-Gallagher, N., et al. (1997). Quantitative analysis of sulci in the hu-
man cerebral cortex: Development, regional heterogeneity, genderdiffer-
Brain Mapping, 5, 218–221.
T. White and C. C. Hilgetag