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Brain structures and networks responsible for stimulation-induced memory flashbacks during forniceal deep brain stimulation for Alzheimer's disease



Introduction: Fornix deep brain stimulation (fx-DBS) is under investigation for treatment of Alzheimer’s disease (AD). We investigated the anatomic correlates of flash-back phenomena that were reported previously during acute diencephalic stimulation. Methods: Thirty-nine patients with mild AD who took part in a prior fx-DBS trial (NCT01608061) were studied. After localizing patients’ implanted electrodes and modeling the volume of tissue activated (VTA) by DBS during systematic stimulation testing, we performed (1) voxel-wise VTA mapping to identify flashback-associated zones; (2) machine learning–based prediction of flashback occurrence given VTA over- lap with specific structures; (3) normative functional connectomics to define flashback- associated brain-wide networks. Results: A distinct diencephalic region was associated with greater flashback likelihood. Fornix, bed nucleus of stria terminalis, and anterior commissure involvement predicted memory events with 72% accuracy. Flashback-inducing stimulation exhibited greater functional connectivity to a network of memory-evoking and autobiographical memory-related sites. Discussion: These results clarify the neuroanatomical substrates of stimulation- evoked flashbacks.
Received: 8 May 2020 Revised: 24 September 2020 Accepted: 22 October 2020
DOI: 10.1002/alz.12238
Brain structures and networks responsible for
stimulation-induced memory flashbacks during forniceal deep
brain stimulation for Alzheimer’s disease
Jürgen Germann1,#Gavin J.B. Elias1,#Alexandre Boutet1,2Keshav Narang1
Clemens Neudorfer1Andreas Horn3Aaron Loh1Wissam Deeb4
Bryan Salvato5Leonardo Almeida4Kelly D. Foote4Paul B. Rosenberg6
David F. Tang-Wai7David A. Wolk8Anna D. Burke9Stephen Salloway10
Marwan N. Sabbagh11 M. Mallar Chakravarty12 Gwenn S. Smith6
Constantine G. Lyketsos6Michael S. Okun4Andres M. Lozano1
1Division of Neurosurgery, Toronto Western Hospital, University Health NetworkUniversity of Toronto, Toronto, Canada
2Joint Department of Medical Imaging, University of Toronto, Toronto, Canada
3Movement Disorders & Neuromodulation Unit, Department for Neurology, Charité – University Medicine Berlin, Berlin, Germany
4Norman Fixel Institute for Neurological Diseases, Departments of Neurology and Neurosurgery, University of Florida Health, USA
5Florida State University, USA
6Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, USA
7Department of Neurology, Toronto Western Hospital, University Health NetworkUniversity of Toronto, Canada
8University of Pennsylvania, USA
9Department of Neurology, Barrow Neurological Institute, Phoenix, USA
10 Department of Psychiatry and Human Behavior and Neurology, Alpert Medical School of Brown University, USA
11 Cleveland Clinic Lou Ruvo Center for Brain Health, USA
12 Douglas Mental Health University Research Institute, Canada
Andres M. Lozano, Toronto Western Hospital,
399 Bathurst Street, Toronto,ON MST 258,
#These authors contributed equally.
Introduction: Fornix deep brain stimulation (fx-DBS) is under investigation for treat-
ment of Alzheimer’s disease (AD). We investigated the anatomic correlates of flash-
back phenomena that were reported previously during acute diencephalic stimulation.
Methods: Thirty-nine patients with mild AD who took part in a prior fx-DBS trial
(NCT01608061) were studied. After localizing patients’ implanted electrodes and
modeling the volume of tissue activated (VTA) by DBS during systematic stimulation
testing, we performed (1) voxel-wise VTA mapping to identify flashback-associated
zones; (2) machine learning–based prediction of flashback occurrence given VTA over-
lap with specific structures; (3) normative functional connectomics to define flashback-
associated brain-wide networks.
Results: A distinct diencephalic region was associated with greater flashback likeli-
hood. Fornix, bed nucleus of stria terminalis, and anterior commissure involvement
predicted memory events with 72% accuracy. Flashback-inducing stimulation exhib-
Alzheimer’s Dement. 2021;1–11. © 2021 the Alzheimer’s Association
ited greater functional connectivity to a network of memory-evoking and autobio-
graphical memory-related sites.
Discussion: These results clarify the neuroanatomical substrates of stimulation-
evoked flashbacks.
Alzheimer’s disease, brain connectivity, deep brain stimulation, fornix, magnetic resonance imag-
ing, memory
Deep brain stimulation targeting the fornix region (fx-DBS) is cur-
rently under investigation for the treatment of Alzheimer’s disease
(AD).1–4 A recent paper reported on acute flashback-like phenomena—
the involuntary recall of autobiographical memories described by ear-
lier authors as “reminiscences”5,6—that were experienced by a subset
of AD patients during initial postoperative fx-DBS programming; these
were associated with specific stimulation settings and appeared to be
unrelated to intrinsic whole-brain or hippocampal volume.7Pioneer-
ing 19th and 20th century experiments involving intraoperative direct
electrical stimulation of the exposed cortex8–12 provided tremendous
insight into the causal relationships between cortical areas and rem-
iniscences, and these insights still stand.5,6 However, the relationship
between these memory phenomena and deep brain structures has not
been systematically investigated and it remains unknown which spe-
cific structures give rise to the flashbacks reported in the aforemen-
tioned fx-DBS population. Although the fornix is the designated tar-
get for therapeutic neuromodulation and is well-known to be a crit-
ical component of the brain’s memory circuits,13–15 the stimulated
region encompasses a number of other white matter tracts and nuclei
that could also conceivably play a role. These include the anterior
commissure,14,16 septal nuclei,17 and bed nucleus of stria terminalis,18
each of which has been implicated in memory function and—like the
fornix—is intimately connected to medial temporal lobe structures like
the hippocampus and entorhinal/perirhinal cortex.19–21
To address this question and further elucidate the architecture of
human memory experience, we investigated the neuroanatomical sub-
strate of stimulation-induced flashbacks in patients with mild AD who
were undergoing bilateral fx-DBS. We hypothesized that the fornix
itself would be a key contributor to this phenomenon. However, given
that the fornix is presumably engaged in most cases of fx-DBS and
yet not all patients experience flashbacks, we expected that nearby
structures might also be necessary substrates. To facilitate this inves-
tigation, we performed (1) volume of tissue activated modeling and
voxel-wise linear modeling of stimulation resulting in memory events
as compared with stimulation without events; (2) machine learning–
based prediction of flashback occurrence given involvement of specific
brain structures; (3) normative resting state functional magnetic res-
onance imaging (rsfMRI) connectomics involving the aforementioned
stimulation volumes; and (4) validation of the normative connectiv-
ity results by comparison with both brain areas previously shown to
elicit flashbacks when electrically stimulated and also with regions and
networks heavily implicated in autobiographical memory and memory
The analysis involved behavioral observations and pre- and postop-
erative structural MRI data from 39 patients with mild AD (Tab l e 1)
who were treated with bilateral fx-DBS as part of a previously
described, 42-patient, multicenter clinical trial ( num-
ber: NCT01608061).3***Each patient who was enrolled in this trial,
which was approved by independent research ethics boards at every
participating site, provided written informed consent. As specified pre-
viously, patients were diagnosed by standardized criteria and expert
examination, with the criteria for mild probable AD being scores of 0.5
TAB L E 1 Patient demographics and baseline clinical characteristics
All patients (n =39)
Patients without
flashbacks (n =21)
Patients with at least one
flashback (n =18)
Age at surgery, mean (SD), years 67.7 (8.0) 67.7 (7.0) 67.7 (9.2)
Sex 19f,20 m 11f, 10 m 8f, 10 m
Baseline Alzheimer’s Disease Assessment
Scale-Cognitive Subscale score, mean (SD)
19.5 (5.6) 19.2, (5.8) 19.9, (5.6)
Disease duration at surgery, mean (SD),
2.1 (1.7) 2.0 (1.7) 2.3 (1.8)
Age at diagnosis, mean (SD), years 65.6 (8.1) 65.7 (7.1) 65.5 (9.4)
Number of patients diagnosed at age <65 14 8 6
1. Systematic Review: Pioneering 19th and 20th century
experiments involving intraoperative direct electrical
brain stimulation provided tremendous insight into the
causal relationships between cortical areas and memory.
As evidenced by recent reviews (Curot et al., 2017, 2020)
and our own inspection of the published literature, few
modern studies have directly built on this research legacy.
2. Interpretation: Our analysis of a serendipitous phe-
nomenon observed during deep brain stimulation (DBS)
of the fornix region allowed us to contribute to this classi-
cal literature, describing specific diencephalic structures–
namely the fornix, anterior commissure, and bed nucleus
of stria terminalis—that predict induction of memory
flashbacks and implicating a network of areas previously
shown to evoke memories when stimulated.
3. Future Directions: These findings help clarify the neu-
roanatomical underpinnings of stimulation-induced flash-
backs. Given that the fornix DBS is under investiga-
tion for its potential to alleviate memory impairment in
Alzheimer’s disease, this insight might inform therapeutic
or 1 on the Clinical Dementia Rating scale and scores of 12-24 on the
Alzheimer’s Disease Assessment Scale-11.22 Additional inclusion and
exclusion criteria for enrollment are outlined in Table S1. All patients
were implanted with bilateral quadripolar (four contacts each) DBS
electrodes (model 3387, Medtronic, Minneapolis, MN) and connected
to an implantable pulse generator23 (Table S2). Of the 42 patients
enrolled in the clinical trial, 3 were excluded due to inadequate image
quality, which precluded precise electrode localization.
During initial postoperative programming of the device, each elec-
trode contact (four per lead) was tested with high-frequency (130 Hz,
90 µs) stimulation beginning at a low voltage (1 volt) and increasing in
1 volt increments up to the maximal voltage tolerated (max =10 volts).
For each contact (eight per patient), if any setting induced a flashback,
the lowest flashback-inducing voltage setting was sampled, along with
the voltage setting(s) immediately below and—if present—above that
did not induce flashbacks. For all contacts without induced memory
events, the largest voltage setting tested was utilized. This conser-
vative selection method was designed to avoid false-positive results.
Classification of memory events was determined using the TEMPau
(Test Episodique de Mémoire du Passé autobiographique) scale.24
Although the quality of reminiscences elicited by electrical stimulation
varies,5this paper’s primary aim was to elucidate the neural correlates
of flashback phenomena in general rather than those underlying sub-
tle variation in memory quality; as such, only presence (TEMPau score
1-4; “memory-yes”) or absence of memory events (TEMPau score 0;
“memory-no”) were considered for analysis.
2.1 Volume of tissue activated modeling
First, we used patient-specific anatomic MRI, stimulation settings, and
volume of tissue activated (VTA) modeling techniques to estimate the
extent of tissue directly modulated by DBS during each observation.
Following non-uniformity correction of all MR images, VTA modeling
was conducted using a well-described pipeline (lead-DBS v2.0; https:
// This involved localization of electrode contacts
on postoperative MRI acquisitions by two experienced users (AH and
GJBE), non-linear normalization to MNI152 standard space (using “low
variance” ANTS ( with an additional sub-
cortical affine transformation when necessary) via coregistered pre-
operative images, and estimation of the shape/extent of the electri-
cal field using finite element method modeling with 0.2 V/mm gra-
dient thresholding (FieldTrip-SimBio pipeline; http://fieldtriptoolbox.
org).25,26 A VTA was estimated for each of the sampled “memory-yes”
and “memory-no” observations using the corresponding stimulation
setting (contact and voltage) and peri-electrode conductivity estimates
(gray matter: 0.33 S/m; white matter: 0.14 S/m; cerebrospinal fluid:
1.79 S/m; electrode contact: 108S/m;insulated electrode components:
1016 S/m) derived from standard space tissue priors. Left-sided VTAs
were flipped in the sagittal plane to facilitate group-level analysis. Fig-
ure 1provides a visual summary of the major neuroimaging processing
steps used in this paper.
2.2 Whole-brain voxel-wise analysis of
flashback-inducing VTAs
Next, “memory-yes” and “memory-no” VTAs were stratified by con-
tact and stimulation voltage in order to examine the possible effects of
these factors independent of VTA location. Simple linear models were
estimated to assess the relationship between contact and voltage, and
between voltage and memory events. Subsequently, whole-brain voxel-
wise logistic regression comparing “memory-yes” and “memory-no”
VTAs was conducted to identify brain areas associated with flashbacks
while controlling for stimulation voltage.
2.3 Support-vector machine classification
Support-vector machine (SVM) learning was then used to further
interrogate the brain structures driving flashbacks and determine
the extent to which their involvement could predict memory events.
Specifically, the presence and extent (in mm3) of overlap between VTAs
and structures (as defined using a manually segmented high-fidelity
diencephalic atlas)27 within memory-associated regions were calcu-
lated and used to classify VTAs as “memory-yes” or “memory-no”. Mod-
eling was performed with balanced data sets of 343 observations for
both “memory-yes” and “memory-no” groups; additional observations
for the “memory-yes” cohort were created by random sampling with
replacement. The most parsimonious model that best classified these
FIGURE 1 Visual summary of
neuroimaging methods. The major
methodological steps (colored arrows) and
their corresponding descriptions are shown
alongside exemplar brain images. First,
patient-acquired pre- and postoperative
anatomic MRI scans were coregistered
together, and each patient’s leads were
precisely localized in patient space based on
the post-operative acquisition (red arrows).
Next, the coregistered patient scans were
normalized to a standard MNI152 template,
and the resultant transforms were used to
warp the lead models to MNI space (green
arrows). VTAs were then modeled for each
“memory-yes/memory-no” observation in
MNI space using the corresponding
stimulation settings and conductivity
estimates from standard space tissue priors
(turquoise arrow). Finally, the created VTAs
(n =386) were employed as (1) inputs for
local voxel-wise mapping analysis (yellow
arrow) and (2) seeds for rsfMRI functional
connectivity mapping (magenta arrow).
MNI =Montreal Neurological Institute;
rsfMRI =resting state functional magnetic
resonance imaging; VTA =volume of tissue
observations was identified and validated using a 10-fold (random split
in 10 balanced (“memory-yes” vs “memory-no”) groups, 3 with 35 mem-
bers per group and 7 with 34) cross-validation approach. In addition,
an alternative model classifying memory events on the basis of voltage
and electrode contact alone was created for comparative purposes.
2.4 Connectomic mapping of flashback-inducing
To investigate wider brain networks associated with flashback-
inducing stimulation, whole-brain connectivity maps were derived for
each VTA using a high-quality normative 3 Tesla rsfMRI data set (http:
// as described previously.25,28–31
Normative data were used for the primary analysis instead of patient-
derived rsfMRI images because the latter were not acquired in the
majority of patients and were of low fidelity (eg, 1.5 Tesla) when
present. Per this connectomic method, correlations with the seed
region (ie, the VTA) were obtained for each voxel in the brain based
on the time course of low-frequency blood oxygen level–dependent
(BOLD) signal fluctuations across 1000 healthy subjects (age range: 18-
35 years; 57% female) (in-house MATLAB script, The MathWorks, Inc.,
Version R2018a. Natick, MA). Whole-brain voxel-wise logistic regres-
sion was then conducted to identify brain areas whose connectedness
was associated with incidence of memory events. Finally, to validate
these normative results, a supplemental connectivity analysis was per-
formed using a disease-specific connectome assembled from 12 AD-
DBS patients with available preoperative rsfMRI imaging.
2.5 Connectomic overlap with canonical memory
To explore how these findings related to the relevant human literature,
we analyzed the spatial overlap between our DBS-induced flashback
functional connectivity network and (1) brain structures identified
through meta-analysis as evoking memory events when stimulated5;
and (2) brain regions whose BOLD response is associated with memory
as per Neurosynth ( meta-analyses of published
task-based fMRI studies.32 For the former, we selected bilateral proba-
bilistic regions-of-interest (ROIs) using a standardized atlas (Harvard-
Oxford cortical-subcortical atlas) in MNI space (Figure 4A).33 For the
latter, we used meta-analytic association maps of voxels linked to auto-
biographical memory and memory retrieval across 84 and 228 pre-
existing fMRI studies, respectively. To assess whether overlap with
these entities was non-random, we permuted the voxels in the DBS-
induced flashback connectivity network 1000 times and determined
the extent of each permutation’s overlap with the aforementioned
ROIs and meta-analytic association maps. As an additional validation,
we used the Neurosynth “decoder” to identify behavioral functional
networks—derived from all available fMRI meta-analyses—with the
greatest spatial similarity to the flashback network.32,34
2.6 Statistics
All statistical analyses were performed using R (v3.4.4; https://www.r- Centre/
RMINC). The pROC (version 1.16.2) package was used to calculate
the receiver-operating characteristic (ROC) curve and the e1071(ver-
sion 1.7-3) package was used for the support vector machine (or
SVM) analysis. Whole-brain correction for multiple comparisons was
performed using the false discovery rate (FDR; voxel-wise threshold
of PFDR <0.05). To strengthen any voxel-wise VTA mapping results
and address the presence of non-independent observations in our
data, we also conducted a non-parametric permutation analysis at
the cluster level. Following a previously described approach, the clin-
ical score associated with each VTA was randomly shuffled across all
lead-contact combinations, creating 10,000 new permuted data sets.
Summary Q statistics were obtained for each data set and the sum-
mary statistic magnitudes of the actual voxel-wise map and the per-
muted maps were compared to discern the validity of the observed
Of the 39 patients included for analysis, 18 (46%) patients experi-
enced flashback phenomena at least once, whereas 21 patients (54%)
never experienced flashbacks. Baseline demographic characteristics
were similar between these two groups of patients (Ta b l e 1). In total,
43 “memory-yes” and 343 “memory-no” observations were sampled,
and a separate VTA was created for each observation. Stratification
of “memory-yes” and “memory-no” VTAs by contact and stimulation
voltage revealed that stimulation delivered from the more dorsal three
contacts (contacts “1-3”) on occasion produced acute memory events,
while stimulation at the ventral-most contact (contact “0”) never did
(Figure 2A). There was a significant effect of contact on voltage, with
mean voltage increasing incrementally as stimulation moved dorsally
(P<0.001, voltage at contacts 0-3 [ventral to dorsal, mean±standard
deviation]: contact 0: 5.16±1.22 volts, contact 1: 5.66±1.61 volts;
contact 2: 6.36±1.99 volts; contact 3: 7.57±2.26 volts). This likely
reflected a greater tendency for stimulation to evoke unpleasant auto-
nomic side-effects at ventral contacts (thus limiting the voltage toler-
ated), which were in proximity to hypothalamic nuclei.7Voltage was
significantly lower for “memory-yes” compared to “memory-no” VTAs
both overall (mean±standard deviation, “memory-yes”: 5.67±2.01
volts; “memory-no”: 6.36±2.05 volts, P<0.01) and individually for
contacts 2 (mean±standard deviation, “memory-yes”: 5.63±1.86 volts;
“memory-no”: 6.54±2.00 volts, P<0.05) and 3 (mean±standard devi-
ation, “memory-yes”: 6.14±2.29 volts; “memory-no”: 7.81±2.18 volts,
P<0.01) (Figure 2B).
3.1 Whole-brain voxel-wise VTA analysis
Using whole-brain voxel-wise logistic regression to investigate the
association of VTA location and memory events, we identified two sig-
nificant clusters (each voxel passed FDR correction at PFDR <0.05):
a dorsal cluster in the anterior diencephalon, impinging on the col-
umn of the fornix, septal region, bed nucleus of stria terminalis (BNST),
and anterior commissure, associated with greater likelihood of mem-
ory events; and a ventral cluster in the hypothalamus associated
with a lower likelihood of memory events (Figure 2C; Table S3). To
confirm that these results were not driven by patient-specific char-
acteristics of individuals who reported memory flashbacks, a linear
mixed-effect model analysis with subject as random variable (repeated
measure design) was performed, looking only at patients who had at
FIGURE 2 Results of voxel-wise VTA mapping of flashback-inducing stimulation. (A) Bar graph showing the number of stimulations (count) at
each contact (ventral to dorsal, “0”to“3”) that did (red) or did not (blue) produce acute memory events. Note that no memory events were
reported during stimulation of the ventral-most contact. (B) Boxplot showing the minimal voltage (memory event, red) and maximal voltage (no
memory event, blue) for the stimulations at each contact. (C) Results of voxel-wise VTA mapping show voxels significantly (PFDR <0.05) positively
(warm colors) and negatively (cool colors) associated with memory flashbacks. Only the dorsal cluster of significant voxels lay within a region
(outlined in green) established as non-random by non-parametric permutation testing (Ppermutation <0.05, n =10,000 permutations). The fornix
(red), BNST (yellow), and anterior commissure (green) are overlaid in faded colors on sagittal (left), coronal (middle), and axial (right) T1-weighted
MNI152 brain slices. BNST =bed nucleus of stria terminalis; FDR =false discovery rate; MNI =Montreal Neurological Institute; VTA =volume of
tissue activated; *P<0.05; **P<0.01
least one memory event. In these patients, we compared each setting
that elicited flashbacks with a matched setting at the same contact,
just below in voltage, that did not elicit flashbacks. This supplemen-
tary analysis, which used threshold-free cluster enhancement38 (TFCE;
voxel threshold of PBonferroni <0.0001) for multiple comparisons cor-
rection, reaffirmed the results of the whole sample analysis, identify-
ing a nearly identical cluster of voxels to be significantly associated
with memory flashbacks (Figure S1). Only the dorsal cluster lay within
a region that was shown by non-parametric permutation testing to be
non-random (Ppermutation <0.05, n =10,000 permutations).
3.2 Support-vector machine classification
SVM modeling reinforced the role of the fornix, BNST, and anterior
commissure in eliciting memory flashbacks upon electrical stimulation.
FIGURE 3 SVM modeling of flashback-inducing stimulation. (A) Three-dimensional rendering of fornix, BNST, and anterior commissure on a
T1-weighted MNI152 brain. (B) Confusion matrix summarizing classification performance of the best SVM, which incorporated voltage as well as
VTA impingement on fornix, BNST, and anterior commissure. (C) Confusion matrix summarizing classification performance of an alternative SVM
that used voltage and contact as components. (D) ROC curves and AUC summary of the best model (see B) and alternative model (see C).
AUC =area under the ROC curve; BNST =bed nucleus of stria terminalis; FNR =false-negative rate; FPR =false-positive rate; MNI =Montreal
Neurological Institute; ROC =receiver-operating characteristic; SVM =support-vector machine; TNR =true-negative rate; TPR =true-positive
A model using stimulation voltage, volume overlap (continuous) with
BNST, and impingement (binary) on fornix and anterior commissure
was found to be most successful at classifying VTAs (Figure 3). This
model achieved 72% accuracy (true-negative rate: 0.68, false-negative
rate: 0.24, false-positive rate: 0.32, true-positive rate: 0.76) and 77%
area under the receiver-operating characteristic (ROC) curve (AUC)
compared to chance performance (50%). The addition of other com-
ponents like the septal region, other diencephalic structures, baseline
Alzheimer’s Disease Assessment Scale-Cognitive Subscale scores, or
demographic features (eg, age or sex) did not improve performance.
The alternative model, which disregarded anatomic structure involve-
ment and used only voltage and electrode contact, performed more
poorly (67% accuracy; true-negative rate: 0.46, false-negative rate:
0.11, false-positive rate: 0.54, true-positive rate: 0.89; 67% AUC). Ten-
fold cross-validation of the best model classified VTAs with 71% accu-
racy (true-negative rate: 0.64, false-negative rate: 0.22, false-positive
rate: 0.36, true-positive rate: 0.78) (Figure S2).
3.3 Connectomic mapping of flashback
Whole-brain voxel-wise logistic regression of the VTA-specific
connectivity maps identified a number of brain areas whose
FIGURE 4 Connectomic mapping of flashback phenomena and comparison with memory-inducing ROIs and regions involved in
autobiographical memory. (A) Results of voxel-wise normative functional connectivity analysis showing significantly (PFDR <0.05) positively (red)
and negatively (blue) connected voxels associated with memory flashbacks are overlaid on sagittal (left), coronal (middle), and axial (right)
T1-weighted MNI152 brain slices. Flashback-inducing stimulation was linked to greater connectivity to the bilateral lateral temporal lobes, medial
temporal lobes, prefrontal regions, cingulate cortex, and insular cortex. (B) Table stating percentage overlap of ROIs at which electrical stimulation
reportedly induces acute memory events (see C) and Neurosynth meta-analytic association maps (see D) with the DBS-induced flashback
connectome (PFDR <0.05). The Pvalue indicating the likelihood that this overlap is random given 1000 permutations of the flashback connectome
is also provided (Ppermutation). (C, D) Axial T1-weighted MNI152 brain slices showing DBS-induced flashback connectome (warm colors) with (C)
ROI outlines (white; labeled—see B), and (D) Neurosynth meta-analytic association maps (green and blue—see B). FDR =false discovery rate;
MNI =Montreal Neurological Institute; n.s.=not significant; ROI =region of interest
connectedness was associated with memory events. Flashback-
inducing stimulation was linked to significantly (each voxel passed
FDR correction at PFDR <0.05) greater connectivity to the bilateral
lateral and medial temporal lobes, prefrontal regions, cingulate cor-
tex, and insular cortex (Figure 4A).Thesesameregionswerealso
significantly related to flashback-inducing stimulation when a disease-
specific connectome was used, corroborating our normative results
(Figure S3).
3.4 Connectomic overlap with canonical memory
The extent of overlap between this DBS-induced flashback con-
nectivity profile and previously reported memory-eliciting ROIs and
memory-related meta-analytic association maps was then calculated.
As verified by permutation testing (n =1000 permutations), con-
siderable non-random overlap was observed between the flashback
connectome and several ROIs (amygdala, hippocampus, middle tem-
poral gyrus, parahippocampal gyrus, and insular cortex) as well as
both the “memory retrieval” and “autobiographical memory” associa-
tion maps (Figure 4B-D). Using the Neurosynth “decoder” we identified
the top five most similar behavioral networks to be “autobiographical”
(r=0.24), “episodic” (r=0.20), “retrieval” (r=0.17), “autobiographical
memory” (r=0.17), and “episodic memory” (r=0.17).
Using VTA modeling and normative functional connectomics, we
uncovered brain areas and networks likely involved in previously
reported stimulation-induced flashback phenomena.7To our knowl-
edge, this is the first systematic experimental analysis of deep subcor-
tical stimulation causing acute reminiscences in humans. This marks a
meaningful step beyond modern causal evidence, which has by neces-
sity derived primarily from animal work or case series of human brain
lesions. In doing so, this study marks a rare addition to the research
legacy of classical 19th and 20th experiments8–12 that meticulously
elucidated the relationship between various brain areas and memory
responses through direct intraoperative stimulation of the exposed
The region of the antero-dorsal diencephalon emerged as important
for inducing memory flashbacks; insights derived from machine learn-
ing moreover suggested that BNST,39,40 fornix,15,41,42 and anterior
commissure,43–45 in particular, contributed to these events. The fact
that a model incorporating overlap with these structures performed
better than an alternative model that relied solely on stimulation volt-
age and contact—specifically avoiding false-positive identification of
flashbacks—emphasizes that the occurrence of memory events cannot
be explained fully by stimulation intensity or relative depth, instead
being more accurately predicted by “hitting” specific neuroanatomical
substrates. All three of these structures have been implicated exten-
sively in memory function.14,15,19,39–45 Of interest, the volume of VTA
overlap appeared to make a difference with respect to flashback induc-
tion for the gray matter structure (BNST) but not for the two white
matter structures. This may reflect the continuous nature of white mat-
ter axons, and the notion that impingement on a circumscribed cross-
section of a given bundle will propagate along its extent.
Through normative rsfMRI mapping, we found that flashback-
associated VTAs were preferentially connected to a wider brain net-
work that primarily comprised the medial and lateral temporal lobes,
prefrontal regions, insular cortex, and cingulate areas. These same
regions are implicated in autobiographical memory recall by prior
brain stimulation work5and functional neuroimaging studies,32 as
well as in a recent normative mapping analysis of brain lesions caus-
ing amnesia.19 Indeed, the BNST, fornix, and anterior commissure are
known to be intimately structurally connected with the medial and
lateral temporal lobes.13,16,18 This, coupled with the converging evi-
dence described here, places these structures at the heart of this puta-
tive recall network and suggests that they may be ideally suited to
evoke autobiographical memory percepts. Future prospective studies
in humans should follow-up on this line of research, seeking to clar-
ify more specific roles for each structure and working to disambiguate
their necessity or sufficiency with regard to flashbacks.
This study does have some limitations. For one, the collection of
behavioral flashback data may have been affected by other AD phe-
nomena such as delusions or disorientation. Other limitations relate
to the neuroimaging methods employed. Finite element method VTA
modeling was used to estimate the size and shape of the electrical
fields generated by DBS. Although this approach utilized standard
space tissue segmentations and conductivity values to approximate the
extent of the electrical field, it remains a simplification of the manner
in which electrical stimulation interfaces with the brain. Nonetheless,
this method has been used in several recent publications25,46 and has
been shown to predict clinical improvement in out-of-sample data.36
In addition, our connectomic analysis was performed primarily using
normative data and thus may have omitted certain idiosyncrasies of
patient- or pathology-specific functional connectivity. This disadvan-
tage is partially offset by a number of clear advantages of norma-
tive data, however. Unlike imaging obtained in patients, which is fre-
quently of suboptimal quality, normative data gathered through ini-
tiatives such as the Brain Genomics Superstruct Project offer supe-
rior spatial resolution and signal-to-noise ratio.32,47,48 Moreover, we
were able to replicate our main connectivity results using a disease-
specific connectome derived from a subset of our AD-DBS patients
who had preoperative rsfMRI data, suggesting that these findings hold
true in this specific population. This fits with recent work by Wang and
colleagues49 that compared the ability of healthy normative, disease-
specific, and patient-specific connectomes to predict Parkinson disease
DBS treatment response, finding that each connectome identified a
similar whole-brain pattern that significantly related to optimal out-
In sum, insights from VTA modeling, machine learning, and norma-
tive functional connectomics indicate that BNST, fornix, and anterior
commissure are key local substrates of flashbacks evoked during fornix
region DBS, and that flashback-inducing stimulation interacts with a
distributed brain network previously implicated in autobiographical
memory retrieval. These findings might provide the basis for future
work investigating therapies to stabilize or improvememory in patients
with dementia.
Jürgen Germann, Gavin J.B. Elias, and Alexandre Boutet conceived the
experiment. Wissam Deeb, Bryan Salvato, Leonardo Almeida, Kelly D.
Foote, Paul B. Rosenberg, David F. Tang-Wai, David A. Wolk, Anna D.
Burke, Stephen Salloway, Marwan N. Sabbagh, M. Mallar Chakravarty,
Gwenn S. Smith, Constantine G. Lyketsos, Michael S. Okun, and Andres
M. Lozano collected the data. Andreas Horn performed MR image
registration and electrode localization. Alexandre Boutet and Keshav
Narang constructed the VTAs. Aaron Loh constructed the patient spe-
cific connectome. Jürgen Germann and Gavin J.B. Elias performed the
data analysis. Jürgen Germann, Gavin J.B. Elias, and Clemens Neudor-
fer wrote the manuscript. All authors edited the manuscript. Andres M.
Lozano supervised the project.
This work was supported by the RR Tasker Chair in Functional Neu-
rosurgery at University Health Network (AML), the Canadian Insti-
tutes of Health Research (reference # 164235: GJBE), and the Ger-
man Research Foundation (Deutsche Forschungsgemeinschaft, DFG
NE 2276/1-1: CN; DFG grant 410169619: AH).
AML is scientific director of Functional Neuromodulation and reports
consultant fees from Medtronic, Abbott, and Boston Scientific. CGL
reports consultant fees from Avanir, Eli Lilly, and the NFL benefits
office. MSO reports consultant fees from the American Academy
of Neurology, Peerview, WebMD/Medscape, and MedEdicus. PBR
reports consultant fees from GLG, Leerink, Otsuka, Avanir, Bionomics,
ITI, IQVIA, and the US Food and Drug Administration. SS reports
research support and consultant fees from Biogen, Lilly, Eisai, Genen-
tech, Roche, Novartis, and Avid. DAW reports consultant fees from
Lilly, Merck, Jannsen, GE Healthcare, and Neuronix. MNS reports con-
sultant fees from Allergan, Biogen, Roche, Genentech, Cortexyme,
Bracket, and Sanofi. The other authors have nothing to disclose.
The data supporting these analyses are available from the correspond-
ing author upon reasonable request.
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Additional supporting information may be found online in the Support-
ing Information section at the end of the article.
How to cite this article: Germann J, Elias GJB, Boutet A, et al.
Brain structures and networks responsible for
stimulation-induced memory flashbacks during forniceal deep
brain stimulation for Alzheimer’s disease. Alzheimer’s Dement.
... Here, the posterior limb of the anterior commissure emerged as a substrate of modulation. This result supports the main findings from Germann et al. 31 , previously associating stimulation of the anterior commissure with the occurrence of flashbacks, using a different methodological approach. A seminal historical article by Wilder Penfield and colleagues 24 associated electrical stimulation of specific sites of the temporal cortex with the occurrence of flashbacks, and this has been recently confirmed by other studies 52 . ...
... There are now completed phase I 25 and II 29 clinical trials (NCT00658125, NCT01608061), as well as an ongoing international randomized-controlled trial (Advance II, NCT03622905). In addition, recent studies investigated the neural substrates underlying memory flashbacks 30,31 and autonomic response 32 reported in this patient population. ...
... In a sub analysis concerning the original hypothesis that led to fx-DBS in AD, we carried out DBS fiber filtering by contrasting stimulation settings that did or did not induce flashback-like phenomena during the surgical procedure 30,31 . On a localized level, this effect had been studied before 30,31 , but not on a tract level. ...
Full-text available
Deep brain stimulation (DBS) to the fornix is an investigational treatment for patients with mild Alzheimer’s Disease. Outcomes from randomized clinical trials have shown that cognitive function improved in some patients but deteriorated in others. This could be explained by variance in electrode placement leading to differential engagement of neural circuits. To investigate this, we performed a post-hoc analysis on a multi-center cohort of 46 patients with DBS to the fornix (NCT00658125, NCT01608061). Using normative structural and functional connectivity data, we found that stimulation of the circuit of Papez and stria terminalis robustly associated with cognitive improvement (R = 0.53, p < 0.001). On a local level, the optimal stimulation site resided at the direct interface between these structures (R = 0.48, p < 0.001). Finally, modulating specific distributed brain networks related to memory accounted for optimal outcomes (R = 0.48, p < 0.001). Findings were robust to multiple cross-validation designs and may define an optimal network target that could refine DBS surgery and programming. Deep brain stimulation has been investigated as a potential treatment for cognitive impairments in Alzheimer’s disease. Here the authors carry out post hoc analysis of multi-center cohorts to investigate the anatomical and functional correlates of effective deep brain stimulation, and find that stimulating circuit of Papez, fornix and bed nucleus of the stria terminalis, and a multi-region functional network, were associated with clinical improvement.
... Among these, 15 were further excluded, as they did not meet the predefined inclusion criteria. Overall, 17 studies were finally included [17][18][19][20][21][22][23][24][25][26][27][28][29][30][31]. Two [17,28] out of these 17 studies were open-label studies reporting no NCT/EUCT code and were analysed separately. ...
... Two [17,28] out of these 17 studies were open-label studies reporting no NCT/EUCT code and were analysed separately. Three NCTs (NCT01094145, NCT02263937, NCT01608061) featured multiple publications and post hoc studies [29][30][31]. The flow diagram of included studies is reported in Fig. 1. ...
Full-text available
Background: Dementia affects more than 55 million people worldwide. Several technologies have been developed to slow cognitive decline: deep brain stimulation (DBS) of network targets in Alzheimer's disease (AD) and dementia with Lewy bodies (DLB) have been recently investigated. Objective: This study aimed to review the characteristics of the populations, protocols, and outcomes of patients with dementia enrolled in clinical trials investigating the feasibility and efficacy of DBS. Materials and methods: A systematic search of all registered RCTs was performed on and EudraCT, while a systematic literature review was conducted on PubMed, Scopus, Cochrane, and APA PsycInfo to identify published trials. Results: The literature search yielded 2122 records, and the clinical trial search 15 records. Overall, 17 studies were included. Two of 17 studies were open-label studies reporting no NCT/EUCT code and were analysed separately. Of 12 studies investigating the role of DBS in AD, we included 5 published RCTs, 2 unregistered open-label (OL) studies, 3 recruiting studies, and 2 unpublished trials with no evidence of completion. The overall risk of bias was assessed as moderate-high. Our review showed significant heterogeneity in the recruited populations regarding age, disease severity, informed consent availability, inclusion, and exclusion criteria. Notably, the standard mean of overall severe adverse events was moderately high (SAEs: 9.10 ± 7.10%). Conclusion: The population investigated is small and heterogeneous, published results from clinical trials are under-represented, severe adverse events not negligible, and cognitive outcomes uncertain. Overall, the validity of these studies requires confirmation based on forthcoming higher-quality clinical trials.
... For these patients, neuromodulation therapies, such as deep brain stimulation (DBS), have been investigated as a possible avenue of treatment (2,(7)(8)(9)(10)(11). DBS is a neurosurgical therapy in which implanted electrodes are used to adjustably deliver electrical current to specific brain targets (12). It is a well established treatment for movement disorders such as Parkinson's Disease, dystonia, and essential tremor, and has recently demonstrated promise for several psychiatric and neurological disorders, including Alzheimer's disease (13,14), epilepsy (15), obsessive-compulsive disorder (16,17), depression and anorexia nervosa (18)(19)(20)(21). ...
... Our connectomics analyses provided interesting insights into the structural and functional networks that underlie the clinical efficacy of pHyp-DBS. As no native functional or diffusion weighted imaging scans were available in the patient population, these analyses were performed using high resolution, high signal-to-noise ratio images derived from healthy individuals (7,13,18,30,52). Although normative connectivity data may not fully capture patient-or pathology-specific variations, they have been previously shown to generate comparable results to patient-specific imaging data (52). ...
Full-text available
Deep brain stimulation targeting the posterior hypothalamus (pHyp-DBS) is being investigated as treatment for refractory aggressive behaviour, but its mechanisms of action remain elusive. We conducted an integrated imaging analysis of a large multi-centre dataset, incorporating volume of activated tissue modeling, probabilistic mapping, normative connectomics, and atlas-derived transcriptomics. 91% of the patients responded positively to treatment, with a more striking improvement recorded in the pediatric population. Probabilistic mapping revealed an optimized surgical target within the posterior-inferior-lateral posterior hypothalamic area and normative connectomic analyses identified fiber tracts and interconnected brain areas associated with sensorimotor function, emotional regulation, and monoamine production. Functional connectivity between the target, periaqueductal gray and the amygdala – together with patient age – was highly predictive of treatment outcome. Finally, transcriptomic analysis showed that genes involved in mechanisms of aggressive behaviour, neuronal communication, plasticity and neuroinflammation may underlie this functional network.
... There are now completed phase I 25 and II 29 clinical trials (NCT00658125, NCT01608061), as well as an ongoing international randomized-controlled trial (Advance II, NCT03622905) 29 . In addition, recent studies investigated the neural substrates underlying memory flashbacks 30,31 and autonomic response 32 reported in this patient population. ...
... like phenomena during the surgical procedure30,31 . On a localized level, this effect had been studied before 30,31 , but not using DBS fiber filtering. ...
Full-text available
Deep brain stimulation (DBS) to the fornix is an investigational treatment option for patients with mild Alzheimer's disease. Outcomes from randomised clinical trials have shown that cognitive function improved in some patients but deteriorated in others. One reason could be variance in electrode placement leading to differential engagement of neural circuits. To investigate this, we analysed a multi-centre cohort of 46 patients with DBS to the fornix. Using normative structural and functional connectivity data, we demonstrate that stimulation of the circuit of Papez and stria terminals robustly associated with cognitive improvement (R = 0.45, p = 0.031). On a local level, the optimal stimulation site resided at the direct interface between these structures (R = 0.33, p = 0.016). Finally, modulating specific distributed brain networks related to memory accounted for optimal outcomes (R = 0.38, p = 0.006). Findings were robust to multiple cross-validation designs and may now define an optimal network target which could subsequently guide refinement of DBS surgery and programming.
... The amnesia was ameliorated, using a neuropsychological battery, posterior to modulation of these targets for 12 months (Laxton et al., 2010). Based on the findings, other researchers have followed this method, obtaining similar results to the ones first published (Fontaine et al., 2013;Sankar et al., 2015;Ponce et al., 2016;Leoutsakos et al., 2018;Germann et al., 2021;Targum et al., 2021;Barcia et al., 2022;Ríos et al., 2022). ...
Full-text available
Limbic surgery is one of the most attractive and retaken fields of functional neurosurgery in the last two decades. Psychiatric surgery emerged from the incipient work of Moniz and Lima lesioning the prefrontal cortex in agitated patients. Since the onset of stereotactic and functional neurosurgery with Spiegel and Wycis, the treatment of mental diseases gave attention to refractory illnesses mainly with the use of thalamotomies. Neurosis and some psychotic symptoms were treated by them. Several indications when lesioning the brain were included: obsessive-compulsive disorder, depression, and aggressiveness among others with a diversity of targets. The indiscriminately use of anatomical sites without enough scientific evidence, and uncertainly defined criteria for selecting patients merged with a deficiency in ethical aspects, brought a lack of procedures for a long time: only select clinics allowed this surgery around the world from 1950 to the 1990s. In 1999, Nuttin et al. began a new chapter in limbic surgery with the use of Deep Brain Stimulation, based on the experience of pain, Parkinson’s disease, and epilepsy. The efforts were focused on different targets to treat depression and obsessive-compulsive disorders. Nevertheless, other diseases were added to use neuromodulation. The goal of this article is to show the new opportunities to treat neuropsychiatric diseases.
... provide each individual information of connectivity of his own brain, and may not reflect his actual situation. It can vary with age, gender, body mass index and neurological diseases [41][42][43][44][45][46]. ...
Full-text available
Historically, the success of DBS depends on the accuracy of electrode localization in neuroanatomical structures. With time, diffusion-weighted magnetic resonance imaging (MRI) and functional MRI have been introduced to study the structural connectivity and functional connectivity in patients with neurodegenerative disorders such as PD. Unlike the traditional lesion-based stimulation theory, this new network stimulation theory suggested that stimulation of specific brain circuits can modulate the pathological network and restore it to its physiological state, hence causing normalization of human brain connectome in PD patients. In this review, we discuss the feasibility of network-based stimulation and the use of connectomic DBS in PD.
... iv) Normative connectomes. While the employment of normative connectomes was able to validate clinical outcome in out-of-sample data (Al-Fatly et al., 2019;Germann et al., 2021;Horn et al., 2017cHorn et al., , 2022Johnson et al., 2020;Li et al., 2020) it is important to note that these datasets lack patient-and pathology-specificity. In contrast to native imaging, however, connectomes offer superior data quality owing to acquisition on specialized hardware, optimized acquisition parameters, and specialized image-processing pipelines (Glasser et al., 2016(Glasser et al., , 2013Yeo et al., 2011). ...
Full-text available
Following its introduction in 2014 and with support of a broad international community, the open-source toolbox Lead-DBS has evolved into a comprehensive neuroimaging platform dedicated to localizing, reconstructing, and visualizing electrodes implanted in the human brain, in the context of deep brain stimulation (DBS) and epilepsy monitoring. Expanding clinical indications for DBS, increasing availability of related research tools, and a growing community of clinician-scientist researchers, however, have led to an ongoing need to maintain, update, and standardize the codebase of Lead-DBS. Major development efforts of the platform in recent years have now yielded an end-to-end solution for DBS-based neuroimaging analysis allowing comprehensive image preprocessing, lead localization, stimulation volume modeling, and statistical analysis within a single tool. The aim of the present manuscript is to introduce fundamental additions to the Lead-DBS pipeline including a deformation warpfield editor and novel algorithms for electrode localization. Furthermore, we introduce a total of three comprehensive tools to map DBS effects to local, tract- and brain network-levels. These updates are demonstrated using a single patient example (for subject-level analysis), as well as a retrospective cohort of 51 Parkinson's disease patients who underwent DBS of the subthalamic nucleus (for group-level analysis). Their applicability is further demonstrated by comparing the various methodological choices and the amount of explained variance in clinical outcomes across analysis streams. Finally, based on an increasing need to standardize folder and file naming specifications across research groups in neuroscience, we introduce the brain imaging data structure (BIDS) derivative standard for Lead-DBS. Thus, this multi-institutional collaborative effort represents an important stage in the evolution of a comprehensive, open-source pipeline for DBS imaging and connectomics.
... It is important to recognize that functional connectivity based on rsfMRI of healthy individuals may not reflect the neural network connectivity in AD patients who have neurodegeneration-related anatomical changes. However, studies comparing patient-specific functional connectivity with normative functional connectivity based on atlases have resulted in the identification of the same networks [60,61]. Thus, our normative functional connectivity analysis may indeed reflect the brain network functional connectivity in AD patients after neuromodulation at the specified targets (fornix, ALIC, NBM, left DLPFC, M1, PMA, SMA, and DMPFC). ...
Full-text available
Abstract Deep brain stimulation (DBS) and non-invasive neuromodulation are currently being investigated for treating network dysfunction in Alzheimer’s Disease (AD). However, due to heterogeneity in techniques and targets, the cognitive outcome and brain network connectivity remain unknown. We performed a systematic review, meta-analysis, and normative functional connectivity to determine the cognitive outcome and brain networks of DBS and non-invasive neuromodulation in AD. PubMed, Embase, and Web of Science were searched using three concepts: dementia, brain connectome, and brain stimulation, with filters for English, human studies, and publication dates 1980–2021. Additional records from were added. Inclusion criteria were AD study with DBS or non-invasive neuromodulation and a cognitive outcome. Exclusion criteria were less than 3-months follow-up, severe dementia, and focused ultrasound intervention. Bias was assessed using Centre for Evidence-Based Medicine levels of evidence. We performed meta-analysis, with subgroup analysis based on type and age at neuromodulation. To determine the patterns of neuromodulation-induced brain network activation, we performed normative functional connectivity using rsfMRI of 1000 healthy subjects. Six studies, with 242 AD patients, met inclusion criteria. On fixed-effect meta-analysis, non-invasive neuromodulation favored baseline, with effect size −0.40(95% [CI], −0.73, −0.06, p = 0.02), while that of DBS was 0.11(95% [CI] −0.34, 0.56, p = 0.63), in favor of DBS. In patients ≥65 years old, DBS improved cognitive outcome, 0.95(95% [CI] 0.31, 1.58, p = 0.004), whereas in patients
Alzheimer's disease (AD) is one of the most common progressive neurodegenerative diseases associated with the degradation of memory and cognitive ability. Current pharmacotherapies show little therapeutic effect in AD treatment and still cannot prevent the pathological progression of AD. Deep brain stimulation (DBS) has shown to enhance memory in morbid obese, epilepsy and traumatic brain injury patients, and cognition in Parkinson's disease (PD) patients deteriorates during DBS off. Some relevant animal studies and clinical trials have been carried out to discuss the DBS treatment for AD. Reviewing the fornix trials, no unified conclusion has been reached about the clinical benefits of DBS in AD, and the dementia ratings scale has not been effectively improved in the long term. However, some patients have presented promising results, such as improved glucose metabolism, increased connectivity in cognition related brain regions and even elevated cognitive function rating scale scores. The fornix plays an important regulatory role in memory, attention, and emotion through its complex fiber projection to cognition-related structures, making it a promising target for DBS for AD treatment. Moreover, the current stereotaxic technique and various evaluation methods have provided references for the operator to select accurate stimulation points. Related adverse events and relatively higher cost in DBS have been emphasized. In this article, we summarize and update the research progression on fornix DBS in AD and seek to provide a reliable reference for subsequent experimental studies on DBS treatment of AD.
Full-text available
The study of the hypothalamus and its topological changes provides valuable insights into underlying physiological and pathological processes. Owing to technological limitations, however, in vivo atlases detailing hypothalamic anatomy are currently lacking in the literature. In this work we aim to overcome this shortcoming by generating a high-resolution in vivo anatomical atlas of the human hypothalamic region. A minimum deformation averaging (MDA) pipeline was employed to produce a normalized, high-resolution template from multimodal magnetic resonance imaging (MRI) datasets. This template was used to delineate hypothalamic (n = 13) and extrahypothalamic (n = 12) gray and white matter structures. The reliability of the atlas was evaluated as a measure for voxel-wise volume overlap among raters. Clinical application was demonstrated by superimposing the atlas into datasets of patients diagnosed with a hypothalamic lesion (n = 1) or undergoing hypothalamic (n = 1) and forniceal (n = 1) deep brain stimulation (DBS). The present template serves as a substrate for segmentation of brain structures, specifically those featuring low contrast. Conversely, the segmented hypothalamic atlas may inform DBS programming procedures and may be employed in volumetric studies.
Full-text available
Brain connectivity profiles seeding from deep brain stimulation (DBS) electrodes have emerged as informative tools to estimate outcome variability across DBS patients. Given the limitations of acquiring and processing patient-specific diffusion-weighted imaging data, a number of studies have employed normative atlases of the human connectome. To date, it remains unclear whether patient-specific connectivity information would strengthen the accuracy of such analyses. Here, we compared similarities and differences between patient-specific, disease-matched and normative structural connectivity data and estimation of clinical improvement that they may generate. Data from 33 patients suffering from Parkinson's Disease who underwent surgery at three different centers were retrospectively collected. Stimulation-dependent connectivity profiles seeding from active contacts were estimated using three modalities, namely either patient-specific diffusion-MRI data, disease-matched or normative group connectome data (acquired in healthy young subjects). Based on these profiles, models of optimal connectivity were constructed and used to estimate the clinical improvement in out of sample data. All three modalities resulted in highly similar optimal connectivity profiles that could largely reproduce findings from prior research based on a novel multi-center cohort. In a data-driven approach that estimated optimal whole-brain connectivity profiles, out-of-sample predictions of clinical improvements were calculated. Using either patient-specific connectivity (R = 0.43 at p = 0.001), an age- and disease-matched group connectome (R = 0.25, p = 0.048) and a normative connectome based on healthy/young subjects (R = 0.31 at p = 0.028), significant predictions could be made and underlying optimal connectivity profiles were highly similar. Our results of patient-specific connectivity and normative connectomes lead to similar main conclusions about which brain areas are associated with clinical improvement. Still, although results were not significantly different, they hint at the fact that patient-specific connectivity may bear the potential of estimating slightly more variance when compared to group connectomes. Furthermore, use of normative connectomes involves datasets with high signal-to-noise acquired on specialized MRI hardware, while clinical datasets as the ones used here may not exactly match their quality. Our findings support the role of DBS electrode connectivity profiles as a promising method to investigate DBS effects and to potentially guide DBS programming.
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From the 1930s through the early 1960s, Wilder Penfield12 collected a large number of memories induced by electrical brain stimulation (EBS) during awake craniotomy. As a result, he was a major contributor to several neuroscientific and neuropsychological concepts of long-term memory. His 1963 paper, which recorded all the cases of memories he induced in his operating room, remains a substantial point of reference in neuroscience in 2019, although some of his interpretations are now debatable. However, it is highly surprising that, since Penfield's12 reports, there has been no other surgical publication on memories induced during awake surgery. In this review, we explore this phenomenon and analyze some of the reasons that might explain it. We hypothesize that the main reasons for lack of subsequent reports are related to changes in operative procedures (ie, use of anesthetics, time constraints, and insufficient debriefings) and changes in EBS parameters, rather than to the sites that are stimulated, the pathology treated, or the tasks used. If reminiscences are still induced, they should be reported in detail to add valuable contributions to the understanding of long-term memory networks, especially memories that are difficult to reproduce in the laboratory, such as autobiographical memories.
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Treatment-resistant epilepsy is a common and debilitating neurological condition, for which neurosurgical cure is possible. Despite undergoing nearly identical ablation procedures however, individuals with treatment-resistant epilepsy frequently exhibit heterogeneous outcomes. We hypothesized that treatment response may be related to the brain regions to which MR-guided laser ablation volumes are functionally connected. To test this, we mapped the resting-state functional connectivity of surgical ablations that either resulted in seizure freedom (N= 11) or did notresult in seizure freedom (N= 16) in over 1,000 normative connectomes.There was no diference seizure outcome with respect to the anatomical location of the ablations, and very little overlap between ablation areas was identifed using the Dice Index.Ablations that did notresultin seizure-freedom were preferentially connected to a number of cortical and subcortical regions, as well as multiple canonical resting-state networks. In contrast, ablations that led to seizure-freedom were more functionally connected to prefrontal cortices. Here, we demonstrate that underlying normative neural circuitry may in part explain heterogenous outcomes following ablation procedures in diferent brain regions. These fndings may ultimately inform target selection for ablative epilepsy surgery based on normative intrinsic connectivity of the targeted volume.
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Treatment-resistant epilepsy is a common and debilitating neurological condition, for which neurosurgical cure is possible. Despite undergoing nearly identical ablation procedures however, individuals with treatment-resistant epilepsy frequently exhibit heterogeneous outcomes. We hypothesized that treatment response may be related to the brain regions to which MR-guided laser ablation volumes are functionally connected. To test this, we mapped the resting-state functional connectivity of surgical ablations that either resulted in seizure freedom (N = 11) or did not result in seizure freedom (N = 16) in over 1,000 normative connectomes. There was no difference seizure outcome with respect to the anatomical location of the ablations, and very little overlap between ablation areas was identified using the Dice Index. Ablations that did not result in seizure-freedom were preferentially connected to a number of cortical and subcortical regions, as well as multiple canonical resting-state networks. In contrast, ablations that led to seizure-freedom were more functionally connected to prefrontal cortices. Here, we demonstrate that underlying normative neural circuitry may in part explain heterogenous outcomes following ablation procedures in different brain regions. These findings may ultimately inform target selection for ablative epilepsy surgery based on normative intrinsic connectivity of the targeted volume.
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Objective: To investigate whether functional sweetspots of deep brain stimulation (DBS) in the subthalamic nucleus (STN) can predict motor improvement in PD patients. Methods: Stimulation effects of 449 DBS settings in 21 PD patients were clinically and quantitatively assessed through standardized monopolar reviews and mapped into standard space. A sweetspot for best motor outcome was determined using voxel-wise and nonparametric permutation statistics. Two independent cohorts were used to investigate whether stimulation overlap with the sweetspot could predict acute motor outcome (10 patients, 163 settings) and long term overall UPDRS-III improvement (63 patients). Results: Significant clusters for suppression of rigidity and akinesia, as well as for overall motor improvement resided around the dorsolateral border of the STN. Overlap of the volume of tissue activated with the sweetspot for overall motor improvement explained R2 =37 % of the variance in acute motor improvement, more than triple to what was explained by overlap with the STN (R2 =9 %) and its sensorimotor subpart (R2 =10 %). In the second independent cohort sweetspot overlap explained R2 =20 % of the variance in long-term UPDRS-III improvement, which was equivalent to the variance explained by overlap to the STN (R2 =21 %) and sensorimotor STN (R2 =19 %). Interpretation: This study is the first to predict clinical improvement of Parkinsonian motor symptoms across cohorts based on local DBS effects only. The new approach revealed a distinct sweetspot for STN-DBS in PD. Stimulation overlap with the sweetspot can predict short- and long-term motor outcome and may be used to guide DBS programming. This article is protected by copyright. All rights reserved.
Recent work indicates that the bed nucleus of the stria terminalis (BNST) is critically involved in the regulation of conditioned fear responses to unpredictable threats. Here we examined whether the involvement of the BNST in contextual fear conditioning in male rats depends on the imminence of shock after placement in the conditioning chamber. Specifically, we hypothesized that the BNST supports contextual freezing after conditioning with delayed, but not imminent, footshock (relative to placement in the context). Rats were implanted with cannulae targeting the BNST and underwent a contextual fear conditioning procedure in which a single footshock unconditioned stimulus (US) was delivered either 1 minute or 9 minutes after the rat was placed in the context; the rats received a total of four identical conditioning sessions over two days, all with equivalent exposure to the context. Contexts associated with either imminent or delayed US onsets produced distinct patterns of freezing and shock-induced activity but freezing in each case was context-dependent. Reversible inactivation of the BNST reduced the expression of contextual freezing in the context paired with delayed (9 min), but not imminent (1 min), footshock onset. Implications of these data are discussed in the light of recent conceptualizations of BNST function, as well as for anxiety behaviors.
Background: Panic attacks affect a sizeable proportion of the population. The neurocircuitry of panic remains incompletely understood. Objective: To investigate the neuroanatomical underpinnings of panic attacks induced by deep brain stimulation (DBS) through (1) connectomic analysis of an obsessive-compulsive disorder patient who experienced panic attacks during inferior thalamic peduncle DBS; (2) appraisal of existing clinical reports on DBS-induced panic attacks. Methods: Panicogenic, ventral contact stimulation was compared with benign stimulation at other contacts using volume of tissue activated (VTA) modelling. Networks associated with the panicogenic zone were investigated using state-of-the-art normative connectivity mapping. In addition, a literature search for prior reports of DBS-induced panic attacks was conducted. Results: Panicogenic VTAs impinged primarily on the tuberal hypothalamus. Compared to non-panicogenic VTAs, panicogenic loci were significantly functionally coupled to limbic and brainstem structures, including periaqueductal grey and amygdala. Previous studies found stimulation of these areas can also provoke panic attacks. Conclusions: DBS in the region of the tuberal hypothalamus elicited panic attacks in a single obsessive-compulsive disorder patient and recruited a network of structures previously implicated in panic pathophysiology, reinforcing the importance of the hypothalamus as a hub of panicogenic circuitry.
Background Whereas transient, self-limiting seizures are an infrequent but known complication of deep brain stimulation (DBS) implantation surgery, stimulation itself has occasionally been reported to result in seizure activity at delayed time points. The neural circuitry implicated in stimulation-induced seizures is unknown. Case Description A 47-year-old woman underwent chronic subcallosal cingulate DBS for treatment of refractory anorexia nervosa and experienced seizure with stimulation onset. Supratherapeutic voltage caused a generalized seizure. The patient subsequently experienced a full recovery. We reviewed the literature for other cases of delayed postoperative DBS seizures associated with stimulation. We also investigated whether the higher voltage may have recruited networks implicated in epilepsy. The supratherapeutic voltage stimulated a larger area and engaged vulnerable networks, including bilateral hippocampi, cingulate gyrus, and temporal lobes. Literature review identified 20 studies reporting delayed seizure after DBS surgery, 13 of which demonstrated a robust association with mostly nonmotor DBS stimulation. Conclusions Nonmotor DBS targets, particularly in patients with epilepsy, may be more vulnerable to stimulation-induced seizures; as such, extra caution should be used when programming stimulation parameters at these DBS targets.
In a trial of stimulation of the fornix and subcallosal regions of the hippocampus involving 42 patients with Alzheimer’s disease, 20 patients reported vivid memory flashbacks. The robustness and complexity of the memories increased with increasing voltage applied to the stimulating electrodes.