NeuroImage: Clinical 6 (2014) 320–326

Contents lists available at ScienceDirect

NeuroImage: Clinical
journal homepage: www.elsevier.com/locate/ynicl

The circuitry of abulia: Insights from functional connectivity MRI
J.S. Siegel a, A.Z. Snyder a,b, N.V. Metcalf a, R.P. Fucetola a, C.D. Hacker a, J.S. Shimony b,
*
G.L. Shulman a, M. Corbetta a,b,c,
a

Department of Neurology, Washington University School of Medicine at Washington University, St. Louis, MO, USA
Mallinckrodt Institute of Radiology, Washington University School of Medicine, Washington University, St. Louis, MO, USA
Department of Anatomy & Neurobiology, Washington University School of Medicine, Washington University, St. Louis, MO, USA

b
c

a r t i c l e

i n f o

Article history:
Received 16 June 2014
Received in revised form 18 September 2014
Accepted 18 September 2014
Available online 23 September 2014
Keywords:
Abulia
Executive function
Anterior cingulate
Functional connectivity
fMRI
apathy

a b s t r a c t
Background: Functional imaging and lesion studies have associated willed behavior with the anterior cingulate
cortex (ACC). Abulia is a syndrome characterized by apathy and deficiency of motivated behavior. Abulia is
most frequently associated with ACC damage, but also occurs following damage to subcortical nuclei (striatum,
globus pallidus, thalamic nuclei). We present resting state functional connectivity MRI (fcMRI) data from an individual who suffered a stroke leading to abulia. We hypothesized that, although structural imaging revealed no
damage to the patient3s ACC, fcMRI would uncover aberrant function in this region and in the relevant cortical
networks.
Methods: Resting state correlations in the patient3s gray matter were compared to those of age-matched controls.
Using a novel method to identify abnormal patterns of functional connectivity in single subjects, we identified
areas and networks with aberrant connectivity.
Results: Networks associated with memory (default mode network) and executive function (cingulo-opercular
network) were abnormal. The patient3s anterior cingulate was among the areas showing aberrant functional connectivity. In a rescan 3 years later, deficits remained stable and fcMRI findings were replicated.
Conclusions: These findings suggest that the aberrant functional connectivity mapping approach described may
be useful for linking stroke symptoms to disrupted network connectivity.
© 2014 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license
(http://creativecommons.org/licenses/by-nc-nd/3.0/).

1. Introduction
Historically, neurologists have struggled to reconcile the principle of
functional localization and the observation that the relationship between behavioral deficits and anatomical damage is only partial. A
more modern view is that functionality is represented in distributed
functional systems and their internal connections. And a growing
body of evidence demonstrates that remote dysfunction can occur in regions functionally connected to – but outside of – the area of lesion.
Resting state functional connectivity magnetic resonance imaging
(fcMRI) can measure widely distributed brain networks and offers a
promising avenue of investigation into ways in which injury and
disease affect the connectivity of the brain. Numerous studies have
found a correspondence between behavioral measures and brain
connectivity (Vaidya and Gordon, 2013). Moreover, previous stroke

* Corresponding author at: Department of Neurology, Washington University School of
Medicine, Box 8111, 4525 Scott Ave, St. Louis, MO 63110, USA.
E-mail address: siegelj@wusm.wustl.edu (J.S. Siegel), avi@npg.wustl.edu (A.Z. Snyder),
metcalfn@npg.wustl.edu (N.V. Metcalf), fucetolar@neuro.wustl.edu (R.P. Fucetola),
hackerc@wusm.wustl.edu (C.D. Hacker), shimonyj@mir.wustl.edu (J.S. Shimony),
gordon@npg.wustl.edu (G.L. Shulman), mau@npg.wustl.edu (M. Corbetta).

research has shown that deficits within attention networks are predictive of spatial neglect and that deficits in motor networks are predictive
of motor deficits (He, 2007; Carter, 2010; Van Meer, 2010). In the
present case study of a patient with abulia following stroke, we employ
fcMRI to map functional abnormalities by comparison with agematched controls.
Abulia is characterized by the lack of spontaneous, goal-directed behavior. Clinically, it falls between apathy and akinetic mutism on a continuum of disorders of drive and motivation (Barris and Schuman,
1953). Abulia is most commonly associated with lesions of the anterior
cingulate cortex (ACC) (Cohen, 1999). This association is consistent
with neuroimaging evidence linking the ACC to the initiation of goaldirected behavior (Carter et al., 1999). However, abulia or some degree
of apathy is also caused by subcortical lesions of the anterior thalamus,
caudate nucleus, globus pallidus, and internal capsule (for a review of
abulia see Vijayaraghavan et al., 2002; Ghoshal et al., 2011; Jorge et al.,
2010). It is therefore likely that a more accurate functional localization
of abulia, and related deficits of willed behavior, involves a networklevel dysfunction. A number of networks (fronto-parietal, cinguloopercular, ventral attention network) have been recently described in
relation to executive control (Corbetta et al., 2008; Dosenbach, 2007;
Seeley, 2007; Vincent et al., 2008).

http://dx.doi.org/10.1016/j.nicl.2014.09.012
2213-1582/© 2014 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).

J.S. Siegel et al. / NeuroImage: Clinical 6 (2014) 320–326

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Fig. 1. AFC methodology schematic. fcMRI data are acquired, preprocessed, and registered to atlas space. For each subject, a correlation matrix is produced comparing every gray matter
voxel to every other gray matter voxel. Each column of the matrix represents one voxel3s full connectivity map. Next, every correlation matrix is compared to every other correlation matrix, column-by-column using spatial correlations, producing an (n + 1) × (n + 1) similarity matrix for each gray matter voxel. For each voxel, a Student t-test is computed to determine if
23 P−C similarity values (green) fell outside of the distribution of the n(n − 1) / 2 or 253 C−C similarity values (brown). Finally, the resultant image is overlaid on the patient3s anatomical
image, creating an aberrant functional connectivity (AFC) map.

This report describes findings in a patient who developed abulia, anterograde amnesia, and left-sided weakness following multiple small
embolic infarcts. The patient sustained small infarcts in various brain regions, but not the ACC. We investigated the neural correlates of abulia in
this patient using fcMRI and a novel analytic strategy designed to

identify atypical functional connectivity both at specific locations and
across brain networks. The method compares observed functional connectivity in individuals against an aged-matched reference group. We
hypothesized that this tool would identify atypical functionality in
abulia-associated cortical areas that were structurally intact.

Fig. 2. FLAIR, aberrant functional connectivity (AFC) map, and correlation maps demonstrate lesion−dysfunction relationship and functional connectivity changes. A) FLAIR images with
red arrows highlighting a lesion in the left anterior thalamus and micro-infarcts elsewhere. Atrophy of the left hippocampus is also evident. B) AFC map, produced using the aberrant functional connectivity method, demonstrates multiple foci of abnormality. Voxels masked out due to structural damage are shown in black (i.e., the left anterior thalamus). C) Correlation
maps demonstrate aberrant functional connectivity. Peaks in the AFC map (circled in B) are used as seeds to generate whole-brain connectivity maps (no lesion mask) for CS02 (top)
and average connectivity maps for the 23 controls (bottom). Talairach coordinates for each correlation map are given in parenthesis. Left: a correlation map placed at the center of the
lesion in controls illustrates ACC connectivity. CS02 demonstrates the expected absence of functional connectivity. Middle and right: red arrows highlight areas of connectivity dropout
in the patient.

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J.S. Siegel et al. / NeuroImage: Clinical 6 (2014) 320–326

2. Case history
A 38-year-old right-handed male lawyer (CS02) presented in the
emergency room in December of 2005 with febrile illness and progressive unresponsiveness. The patient was hypoxemic and in septic shock
secondary to infectious endocarditis of the aortic and mitral valves. CT
and MRI revealed multiple small embolic strokes as well as a left subdural hematoma. CS02 remained in a vegetative state for several
weeks. He underwent aortic and mitral valve replacement 6 weeks
post-onset, and acute inpatient rehabilitation at the Rehabilitation Institute of St. Louis for about 3 weeks. He continued to show improvements
in cognitive function over the subsequent 3 months. FLAIR MRI images
taken about 3 months post-onset showed areas of hyper-intensity in
the left hippocampal formation, anterior thalamus, and inferior parietal
lobe. Other lesions were present in the right occipital lobe, bilateral
basal ganglia, right motor cortex, and right cerebellum.
Subsequent evaluations indicated that the patient3s residual deficits
included abulia, anterograde amnesia, left motor weakness and left
homonymous upper quadrantanopia. This clinical picture was stable
from May 2006 through the dates of functional imaging and neuropsychological assessment in October 2009 and again in December 2012.
Before the illness, CS02 was a highly intelligent, successful district attorney, with an active social life. He was passionate about history, baseball, and was an excellent golfer. After his illness, he was unable to
return to the practice of law or live independently. He currently lives
with his parents, manages his own finances, and spends his time reading
and watching television. He still enjoys playing golf and remains a skilled
golfer. He likes to exercise and will participate in cardio-vascular training
if brought to a gymnasium. He is well groomed and socially appropriate,
but rarely speaks spontaneously. When addressed, he answers tersely
and concretely. His emotional range is restricted with absent or minimal
positive or negative affect. He will engage in a game of catch as long as
balls are thrown to him. He retains an excellent memory for past events,
facts, and pictures, but he has trouble learning new verbal information.
He retains an interest in baseball statistics, which he continues to acquire.
For the last 7 years (2006–2013), CS02 has been seen twice a year in
the Cognitive Neurology Clinic (Dr. Corbetta). CSO2 has been tried on
multiple medications in isolation or combination including dopaminergic agonists (L-Dopa; amantadine); stimulants (methylphenidate;
nicotine); a cholinergic agent (donepezil); and, a nootropic agent
(piracetam) with no significant change in his behavior.

Supplementary methods and Fig. 1 for a detailed description of this approach). Voxel-wise correlation matrices were computed by correlating
the time series within each gray-matter voxel (excluding those lesioned
in the patient) against all other gray-matter voxels. For each voxel in the
patient, the correlation map was compared to that of each control subject using spatial correlation. This comparison generated a t-statistic
map representing the degree to which the patient differed from the reference population. To evaluate statistical significance, the same analysis
was performed on the controls, treating each of the control subjects
as a surrogate patient. The resulting AFC maps were explored using a
1) seed-based analysis and 2) a network-based analysis. In both cases,
a t-score threshold (t = 4.8) was chosen to define ‘AFC+’ voxels based
on significance after multiple comparisons correction (p = 1.3e−6).
The Yeo (2011) seven-network cortical map was used to define networks (Yeo, 2011). Six sub-networks were included: the default mode
Table 1
Neuropsychological data. Normalized scores are based on an age and demographic adjusted population with a mean of 50 and a standard deviation of 10. In rows in which two
scores are given, the first is performance at scan 1 (2009) and the second is performance
at scan 2 (2012). In all other rows, data were only available from 2012. Indices for
which the patient fell outside the confidence interval of healthy controls are highlighted.
D-KEFS = Delis−Kaplan executive function system; BVMT = brief visuospatial memory
test; HVLT = Hopkins verbal learning test.
Patient score
Self-rating

Family rating

Executive function

Memory

3. Methods
3.1. Subjects and MRI acquisition and preprocessing
Motor

CS02, and 23 control subjects within 10 years of age of the patient
and without any neurologic or psychiatric history were studied. All participants provided informed consent in accordance with the Declaration
of Helsinki. All study procedures were approved by the Washington
University School of Medicine (WUSM) Institutional Review Board.
CS02, as well as 14 of the 23 control subjects, underwent a comprehensive neuropsychological and behavioral evaluation in the domains of
language, memory, attention, and motor function at the time of the
fMRI. CS02 additionally underwent campimetry to identify visual field
cuts. All structural and resting state scans were acquired on a Siemens
Tim-Trio 3 T Scanner. Scanning parameters were identical for both of
the patient3s visits and for all controls. Following atlas transformation
of all fMRI data, functional connectivity was assessed in CS02 and all
controls within a mask that included gray matter voxels and excluded
areas of lesion (see Supplementary methods).
3.2. Aberrant functional connectivity
Aberrant functional connectivity (AFC) mapping is a novel approach
that compares an individual (i.e., the patient) to healthy controls (see

Language

Attention

Social cognition

Apathy
Disinhibition
Executive dysfunction
Total Score
Apathy
Disinhibition
Executive dysfunction
Total score
Animal naming
WISC-III mazes
Iowa gambling test
D-KEFS word context
D-KEFS tower test
D-KEFS letter fluency
Category fluency
Category switching
BVMT total immediate recall
BVMT learning
BVMT delayed recall
HVLT learning
HVLT total immediate recall
HVLT delayed recall
HVLT recognition hits
Spatial span forward
Spatial span backward
Grip strength L hand (kg)
Grip strength R hand (kg)
9-Hole peg L (pegs/second)
9-Hole peg R (pegs/second)
Motricity index left leg
Motricity index right leg
Combined index FIM walk + timed walk
Word comprehension
Commands
Complex ideational material
Boston naming test
Oral reading of sentences
Comprehension of oral reading of sentences
Nonword reading
Stem completion
Mesulam total misses
Posner RT
Posner accuracy
Posner RT VF effect
Posner RT validity effect
Affect naming
Prosody comprehension
Pairs comprehension
Faces immediate recognition
Faces delayed recognition

68
58
67
67
110
55
75
85
21, 33
48
41
47
37
33
20
27
53, 55
60, 47
61, 57
33, 46
32, 29
13, 18
−14, 17
44, 49
65, 45
40, 41
56, 46
28, 21
63, 61
−88, −97
53, 53
15, 15
59, 48
53, 53
60, 2
53, 53
57, 57
53, 15
57, 57
60, 60
59, 45
56, 55
55, 55
56, 57
65, 67
50
57
50
33
43

J.S. Siegel et al. / NeuroImage: Clinical 6 (2014) 320–326

network (DMN), cingulo-opercular network (CON), motor network,
dorsal attention network (DAN), fronto-parietal network (FPN), and
visual network. The seventh network was excluded as it is comprised
of ventral areas affected by susceptibility inhomogeneity artifact
(Ojemann, 1997). The AFC map was thresholded and voxels were tallied
according to network affiliation. In the region-based analysis, a peak
finding algorithm was applied to the AFC map to define spherical regions of interest (ROIs) that showed significant difference from controls
(high AFC scores). ROIs were then used to generate correlation maps.
Seed-based correlation maps enabled qualitative inspection of FC
abnormalities.
A number of follow-up experiments were run to validate the AFC results. CS02 was brought back for additional functional imaging and neuropsychological testing evaluation 3 years after the initial scan. After
masking out non-brain and lesioned voxels, spatial correlation between
pairs of AFC maps was computed. Both fcMRI scans were split in half
and within-scan correlation (between AFC maps generated with data
from halves of the scan) and between-scan (between AFC maps
generated 3 years apart) correlations were computed. Additionally, A
2-flourodeoxy-D-glucose (FDG) positron emission tomography (PET)
scan of CS02 was obtained using a Siemens EXACT 962 HR+ scanner
while the patient was resting with his eyes closed.

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(Fig. 1). The patient was individually compared to every control on a
column-by-column basis using spatial correlation, thereby producing a
patient-to-control (P−C) similarity image (1 × 34,428). The same comparison was computed between every pair of controls, producing
n ⋅ (n − 1) / 2 control-to-control C−C similarity images. For each of
the 34,428 voxels, a Student t-test was computed comparing P−C
values to C−C values. The t-test was chosen after both groups
were shown to have normally distributed data (not shown). An image
of t-scores throughout the brain could then be overlaid on the patient3s
anatomical image, creating an aberrant functional connectivity
map (AFC map). A t-score threshold (t = 4.8) was chosen to define
‘AFC+’ voxels by calculating significance after multiple comparisons
(p = 1.3e−6).
Inline Supplementary Table S1 can be found online at http://dx.doi.
org/10.1016/j.nicl.2014.09.012.
Fig. 2B shows the patient3s AFC t-score map. Overall, the patient
showed greater number of AFC+ voxels than 22 out of the 23 controls
(Fig. S1B). Areas of aberrant functional connectivity (AFC+) were observed near as well as distant to structural lesions. Regions showing aberrant functional connectivity included the left hippocampus, left
thalamus surrounding the thalamic lesion, left inferior parietal lobule,
and anterior cingulate cortex.

4. Results
4.3. Seed-based correlation mapping
4.1. Neuropsychological evaluation identified abulia and anterograde
amnesia
The patient showed low scores on standardized measures of executive functions, as well as anterograde verbal memory and left-sided
motor deficits (Table 1). The patient self-reported mild elevations in apathy and executive dysfunction, but collateral sources reported far more
significant apathy. On the basis of these results and clinical evaluation, a
diagnosis was made of abulia and moderate anterograde amnesia.
4.2. Aberrant functional connectivity (AFC)
Quality control metrics confirmed that atlas registration, fMRI signal
properties, subject head motion, and brain-wide functional connectivity
were within the range of the 23 controls (Table S1). The ‘patient’ correlation matrix was then compared to ‘control’ correlation matrices

A subset of AFC+ regions (red circles in Fig. 2B) was selected to represent resting state networks that, in subsequent analyses, were shown
to be especially aberrant in this patient. These regions were used to generate correlations maps to elucidate changes to functional connectivity
patterns in AFC+ regions (Fig. 2C). The left panel in Fig. 2C shows the
correlation map corresponding to a seed in the lesioned left thalamus.
The result obtained in the controls demonstrates functional connectivity with the anterior cingulate cortex in addition to the homotopic thalamus. By comparison, the result obtained in CS02 demonstrates the
expected absence of functional connectivity. The middle panel shows
maps obtained with a seed in the inferior parietal lobule. Controls
show a well-defined DMN including anticorrelations with the cinguloopercular network (CON). CS02 shows a less well-defined DMN with
abnormal anticorrelation between the IPL and the frontal pole. The
right panel shows maps obtained with a seed in the ACC. Controls

Fig. 3. Left DMN, CON, and motor networks show the largest degree of disruption. Voxels with significant AFC scores are classified based on the seven-network parcellation of Yeo (2011).
Networks are additionally split by hemisphere (hemi-networks). In order to account for difference in network sizes, results are displayed as the percent of each network with AFC t-score
greater than 4.8. Light gray bars display CS02 AFC results averaged over visits 1 and 2. White bars represent the network breakdown of aberrant functional connectivity in the 23 controls.
Error lines represent upper 95% confidence intervals. Asterisks indicate hemi-networks in which CS02 shows disruption outside of the 95% CI of controls. The parcellation includes
default mode network (DMN), cingulo-opercular network (CON), motor network, dorsal attention network (DAN), fronto-parietal network (FPN), and visual network. The total percent
of AFC+ voxels in the patient and controls is shown in the far right.

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Fig. 4. Reproducibility of AFC maps at 3 year follow up. A) A visual comparison of AFC results from visit 1 and visit 2. The Pearson correlation between AFC maps is 0.5937. B) Pearson
correlations for CS02 between AFC maps generated from half scans (‘within scan’) and AFC maps generated 3 years apart (‘between scan’) are shown and spatial correlation between different control subjects3 AFC maps (‘between subjects’) is given as a control. Correlations between halves were 0.81 and 0.80 for visits 1 and 2 respectively.

show a well-defined CON, with strong bilateral anterior insula functional connectivity with the dorsal ACC. None of these features are evident
in CS02. Instead, CS02 shows diffuse connectivity with anterior portions
of the frontal lobe. For comparison, some single control subject correlation maps are shown in Fig. S3. Fig. S3 additionally shows connectivity
from the AFC+ left anterior thalamus is disrupted for CS02 relative
controls.
4.4. Network-based analysis
Distribution of AFC+ voxels across a seven network parcellations
was assessed. Results were averaged between the patient3s two visits
and compared to averages across the 23 controls (Yeo, 2011). When
measured as percentage of network disrupted, the left default, bilateral
cingulo-opercular, right motor network, and right visual network
showed significant abnormality compared to controls (Fig. 3). In controls, roughly 5% of voxels were above the AFC+ threshold. On average,
these were evenly distributed across the resting state networks.
4.5. Rescan and within-scan validation
The within-scan spatial correlation was 0.81 and 0.80 for visits one
and two respectively. The between-scan (3 years apart) spatial correlation was 0.60. Dominant patterns of aberrant functional connectivity
remained qualitatively similar (Fig. 4A). For comparison, spatial correlation between control subjects3 AFC maps was measured. Spatial correlation between pairs of controls was 0.01 (s.d. = 0.07), demonstrating
that within-scan and between-scan correlation for CS02 is well above
between-subject correlation (Fig. 4B). These results show that AFC results in CS02 are consistent and reproducible.
AFC t-score distributions were generated for both scans of
CS02 (Fig. S1) and for controls. A t-test comparing rightward skewness between CS02 (both scans) and 23 controls yielded p = 0.0565
(t = 1.6579, df = 23). This result means that the number of AFC+
voxels throughout the brain of CS02 was greater than that of controls,
although the difference did not reach statistical significance.
Inline Supplementary Fig. S1 can be found online at http://dx.doi.
org/10.1016/j.nicl.2014.09.012.
4.6. Positron emission tomography
FDG PET scans were acquired to compare functional connectivity to
metabolic activity (Fig. S2). No significant relationship between PETFDG and AFC scores was observed (p-value = 0.274).

Inline Supplementary Fig. S2 can be found online at http://dx.doi.
org/10.1016/j.nicl.2014.09.012.
5. Discussion
Abulia is most commonly associated with lesions of the anterior cingulate cortex (ACC), but also has been described in association with a
variety of subcortical lesions (Vijayaraghavan et al., 2002; Ghoshal
et al., 2011; Jorge et al., 2010). These observations raise the question
of whether common circuitry is disrupted by both types of lesion. It
has been suggested that disconnections of limbic tracts projecting
from the anterior thalamus to the cingulate might cause abulia (Mega
and Cummings, 1994; Mega and Cohenour, 1997). This is the first
study to directly support this hypothesis. Our findings suggest that,
even in the absence of cingulate damage, abulia with anterograde amnesia is associated with disruption of functional network organization
including the cingulate cortex. Furthermore, among the various recently
proposed ‘executive’ networks (Corbetta et al., 2008; Dosenbach, 2007;
Seeley, 2007; Vincent et al., 2008), AFC identified the cingulo-opercular
network as most closely affected in a case in which motivational behavior is severely disrupted.
5.1. Case summary — links to behavior
CS02 sustained multiple embolic strokes that resulted in profound
abulia, anterograde amnesia, left motor weakness, and left homonymous upper quadrantanopia. Some of these deficits could be explained
in terms of focal damage (i.e., left hippocampal atrophy and anterograde
amnesia). With respect to abulia the link was less clear. We speculate
that the patient3s neurologic status is better characterized by networklevel disruption of functional organization, and not just for abulia. The
association of right motor network AFC with left hemiparesis and of
right visual network AFC with a left visual field cut seems apparent.
The resting state network correlates of abulia and amnesia likely involve
multiple networks and cannot be determined on the basis of a single
case that is clinically complex. Possible implications of default mode
network and cingulo-opercular network disruption are considered
below.
Some AFC+ peaks were adjacent to structural lesions; but others,
such as left lateral posterior parietal cortex and dorsal ACC, were not. Elevated AFC scores could result from disconnection caused by damaged
cortex or white matter tracts, but correlation maps from AFC peaks suggest that this is not the case. For example, functional connections between ACC and bilateral insula were disrupted despite the absence of

J.S. Siegel et al. / NeuroImage: Clinical 6 (2014) 320–326

direct damage to ACC, insula, or the interconnecting white matter tracts.
Similar considerations apply to inferior parietal lobule and ventromedial prefrontal cortex (Fig. 2C).
5.2. Cingulo-opercular network (CON)
The CON includes the anterior cingulate, bilateral anterior insula,
and bilateral anterior thalami (Corbetta et al., 2008; Dosenbach, 2007;
Seeley, 2007; Vincent et al., 2008). This network is partially overlapping
with other networks putatively related to executive control: frontoparietal, ventral attention network, and salience network. The CON is
implicated in task initiation, task switching, and conflict monitoring.
FC strength between the ACC and the rest of the CON directly correlates
with performance on a range of executive function tasks involving
working memory, attention, inhibitory control, fluency, and task
switching (Onoda et al., 2012).
The anterior cingulate receives input from the anterior thalamus
(Papez, 1937) and has been associated with willed action across a variety of paradigms and a variety of imaging modalities (Carter et al., 1999;
Bush et al., 2000; Jahanshahi, 1998). Theoretical models of willed action
have been formulated in terms of exploration of the environment
(Swanson, 2000) and determining actions necessary to obtain desired
goals (Carter et al., 1999; Luu et al., 2003). A recent report in patients
with implanted electrodes indicates that stimulation of dorsal ACC cortex leads to ‘feelings of strong motivation and willingness’ (Parvizi et al.,
2013). Our patient demonstrates the converse; functional disruption of
the ACC has led to an amotivational state. Together, these findings highlight the critical role of the ACC, and CO network, in willed action.
Inline Supplementary Fig. S3 can be found online at http://dx.doi.
org/10.1016/j.nicl.2014.09.012.

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and global connectedness to that of controls. Although conceptually
similar, our approach differs in that the spatial pattern of functional connectivity of a given region (functional connectivity ‘fingerprint’) is compared to controls. This strategy allows for the possibility that a region3s
functional connectivity fingerprint may be altered despite no change in
sum connectedness. Further comparisons are needed to determine the
extent to which ‘aberrant’ regions identified by these approaches differ.
The patient presented herein had multiple lesions and structural
changes. Structural alterations make registration challenging.
However, in our experience, adequate atlas transformation
(misregistration b 2 mm) is possible even in cases with large lesions
provided that the lesion is segmented and masked out of the registration computations (He, 2007). AFC+ regions (Fig. S2) had normal FDG
PET scores, suggesting that these regions were in gray matter, and
therefore, not identified as abnormal owing to misregistration.
Our patient3s total AFC score fell within the tail of the control distribution (Fig. S1B). However, we have not here demonstrated that this
measure can reliably distinguish patients from controls. We attribute
this limitation to the small sample size, limited signal to noise ratio of
functional connectivity data, and natural variability within the population (Mueller, 2013). A much larger subject sample would be needed
to determine if the AFC approach can be used to differentiate affected
individuals from the normal population. Future technical improvements
in resting state fMRI (Uğurbil, 2013) most likely will contribute to making the AFC approach more robust.
Nevertheless, our AFC technique reproducibly localized aberrant
functional connectivity within an individual (Fig. 4). We believe that
AFC has illuminated the pathophysiology of abulia in a patient without
ACC structural damage. Moreover, our results illustrate the utility of
functional imaging as a means of improving the understanding of neurologic deficits.

5.3. Default mode network
The DMN is implicated in introspection, prospection, social cognition
and memory (for a review see Buckner et al., 2008). Previous work has
shown that the hippocampus is functionally coupled within the DMN
(Vincent et al., 2006), and DMN resting state functional connectivity
has consistently shown association with memory encoding and recall
(Sestieri et al., 2011). Changes to DMN functional connectivity have
been observed in amnesic patients (Hayes et al., 2012) and reduced
DMN connectivity has been reported in patients with memoryassociated conditions such as Alzheimer3s disease (Greicius et al.,
2004). A prior study on a case of abulia and amnesia similarly found decreased ipsilateral default network connectivity (Jones, 2011). Interestingly, cases of left anterior thalamic lesions causing abulia appear to
consistently show comorbid memory deficit (Nishio et al., 2011). Our
interpretation is that disruption of DMN functional connectivity is related to the patient3s anterograde amnesia. The patient3s DMN AFC was
lateralized to the left hemisphere. Correspondingly, CS02 exhibits a verbal memory deficit, but not a visuospatial memory deficit (Table 1)
(Kelley et al., 1998).
5.4. Limitations and conclusions
This paper demonstrates the use of fcMRI in an individual. Challenges to such an approach arise from normal individual variability in
brain function and brain anatomy. But recent work has shown that reliable identification of resting state network topography within individuals is possible (Hacker et al., 2013; Mennes, 2010). To the extent that
normality can be defined in resting state network terms, fcMRI can potentially offer a non-invasive tool for identifying disruption to function
and network structure. Not withstanding these advantages, a single
case is insufficient to demonstrate a link between network dysfunction
and clinical deficit.
Our approach was inspired by Stufflebeam et al. (2011), who identified epileptogenic foci in individuals by comparing each voxel3s local

Acknowledgements
The authors disclose receipt of the following financial support for the
research and/or authorship of this article: this study was supported
by the National Institute of Health National Research Science
award 5T32GM007200-39, and National Institute of Mental Health
5R01HD061117-07 and the National Institute of Health Medical Scientist training award 5T32GM007200-40. Additional thanks to Lenny
Ramsey, Jonathan Power, Gagan Wig, and Tim Laumann for guidance
and code and Jennifer Rengachary for technical assistance (all in
Washington University Department of Neurology).
Appendix A. Supplementary data
Supplementary data to this article can be found online at http://dx.
doi.org/10.1016/j.nicl.2014.09.012.
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