and temporal profiles of these coupled oscillatory
events are compatible with the SWR-triggered
HFB activation we observed.
Consistent with rodent studies reporting higher
SWR rates during exploration of novel environ-
ments than of familiar ones ( 14 ), we observed a
significantly higher increase in average SWR
rate in response to the first presentation of each
picture than for subsequent presentations of the
same pictures. Unlike SWR activity evoked by
repeated presentations, SWR rates during novel
presentations were not reinstated during the
subsequent recall. This pattern of results sug-
gests the involvement of two different subtypes
of SWRs elicited during viewing: one that reflects
the general processing of novel information and
another that reflects a mnemonic process that is
more content-specific in nature (i.e., recognition
memory, pattern retrieval, etc.). However, it is
important to note, more generally, that processes
of memory retrieval may be closely linked to
processes of memory consolidation (and recon-
solidation), so the observed changes in ripple
rate may underlie both processes ( 14 ).
Together, our results demonstrate an impor-
tant link between SWRs and verbally reported
human episodic memory. More specifically, they
reveal SWR-related reinstatement of visual rep-
resentations during free recall. These results
point to a process by which SWRs set up an
integrated, content-specific dialogue between the
hippocampus and the cortex that initiates and
enables the process of recall.
Methods
Participants
Intracranial recordings were obtained from 15
patients with pharmacologically resistant epi-
lepsy (10 females) at the North Shore University
Hospital, New York. The age of the patients
ranged from 22 to 57 (mean = 36.6, SD = 10.7).
All patients were implanted with subdural in-
tracranial electrodes for diagnostic purposes as
part of their evaluation for neurosurgical epi-
lepsy treatment. All participants performed the
task in their native language (12 English speak-
ers, three Spanish speakers). No clinical seizures
occurred during the experimental duration. The
study was conducted according to the latest
version of the Declaration of Helsinki, and all
participants provided a fully informed consent
according to NIH guidelines, as monitored by
the institutional review board at the Feinstein
Institute for Medical Research.
Experimental task
The experiment was divided into two runs. Each
run began with a closed-eyes resting-state pe-
riod of 200 s (the first two patients performed
the resting state on a different day). Immediately
afterward, participants were presented with
14 different pictures of famous faces and places
(seven in each category; see Fig. 1 for example
stimuli). Picture duration was 1500 ms with
750-ms interstimulus intervals. Each item re-
peated four times in a pseudorandom order,
such that each presentation cycle contained
all pictures but the order of pictures was ran-
domized within the cycle. The same picture
was never presented twice consecutively. Par-
ticipants were instructed to look carefully at the
pictures and try to remember them in detail,
emphasizing unique colors, face expressions,
perspective, lighting, etc. Stimuli were presented
on a standard LCD screen using Presentation
software (picture size: 16.5° × 12.7° at ~60 cm
viewing distance). After viewing the pictures,
participants put on a blindfold and began a
short interference task of counting back from
150 in steps of 5 for approximately 1 min. Upon
completion, recall instructions were presented.
The patients were asked to freely recall as many
pictures as possible while focusing on one cat-
egory at a time, starting with faces in the first
run and with places in the second run.
We instructed the patients to describe each
picture they recalled, as soon as it came to mind,
with two or three prominent visual features.
This was done to ensure that the patients also
retrieved episodic visual information specific to
the studied items, and not just general semantic
details. The duration of the free-recall phase
was 2.5 min per each category (5 min in total ×
two runs). In case the patients indicated that they
were“through,”they received a standard prompt
from the experimenter (e.g.,“Can you remember
any more pictures?”). Each run included a new set
of pictures, and the order of recalled categories
was counterbalanced between the runs.Identification of verbal recall events
Verbal responses during the free-recall phase
were continuously recorded using a microphone
attached to the patient’s gown. The onset and
offset of each recall event were extracted in an
offline analysis, identifying the first/last sound
wave relevant to each utterance ( 44 ), using Au-
dacity recording and editing software (version
2.0.6). SWR events occurring during the verbally
reported recall events, or in the 3 s that imme-
diately preceded the events, were associated with
the item that the patient described. SWR events
that occurred in between recall events were re-
garded as“memory search”ripples and were as-
sociated only with the category that patient was
instructed to recall in the beginning of the free-
recall block.Intracranial recordings
Intracranial recording sites were subdural grids,
strips, or depth electrodes (Ad-Tech, Racine,
WI; Integra, Plainsboro, NJ; PMT Corporation,
Chanhassen, MN). Recording sites in the sub-
dural grids and strips were 1- or 3-mm platinum
disks with 4- or 10-mm intercontact spacing.
Recording sites in depth electrodes implanted in
the hippocampus were 2-mm platinum cylinders
with 4.4-mm intercontact spacing and a diame-
ter of 0.8 mm (see Fig. 1C). During the record-
ings, the intracranial EEGsignal was referenced
to a vertex screw/subdermal electrode and was
filtered electronically between 0.1 and 200 Hz.
The signal was then digitized at 500 Hz/512 Hz
andstoredforofflineanalysisusingXLTEKEMU128FS/NeuroLink IP 256 systems (Natus
Medical Inc., San Carlos, CA). Stimulus-triggered
electrical pulses were recorded along with the
iEEG data for precise synchronization with
stimulus onset. All recordings were conducted
at the patients’quiet bedside.Electrode localization
Prior to electrode implantation, we obtained for
each patient a T1-weighted 1-mm isometric struc-
tural MRI scan using a 3-T scanner. After implan-
tation, a CT scan and a T1-weighted structural
MRI scan at 1.5 T were acquired. The post-
implantation CT and MRI scans were skull-
stripped and co-registered to the preoperative
anatomical MRI scan using FSL’s BET and FLIRT
algorithms ( 64 – 66 ). Concatenating these two
co-registrations allowed visualization of the CT
scan on top of the preoperative MRI scan while
minimizing localization error due to potential
brain shift caused by surgery and implantation.
Individual recoding sites were then identified
visually on the co-registered CT and were marked
in each subject’s preoperative MRI native space
using BioImage Suite ( 67 ).
Next, preoperative structural MRI scans were
processed using FreeSurfer 6.0 ( 68 )tosegment
and reconstruct the cortical surface and hippo-
campal subfields in each patient. Following our
previously published procedure ( 44 , 69 ), the three-
dimensional mesh of the cortical surface in each
patient was resampled and standardized using
SUMA ( 70 ), allowing us to establish node-to-
node correspondence across different surfaces.
This enabled us to visualize electrodes from
different patients on a single cortical template
(“fsaverage”) while adhering to the electrodes’
location in relation to individual gyri and sulci.
Finally, each cortical surface was registered onto
different anatomical atlases ( 54 , 55 ) available
in FreeSurfer, including a probabilistic atlas of
visual retinotopy ( 53 ).Preprocessing and data analysis
All data analysis was performed in MATLAB
2014a/2018b (MathWorks Inc., Natick, MA) using
EEGLAB ( 71 ), Chronux ( 72 ), DRtoolbox (https://
lvdmaaten.github.io/drtoolbox/), MES toolbox
( 52 ), and custom-developed analysis routines.
Raw iEEG data were inspected visually and
statistically to detect noisy/corrupted channels
and exclude them from further analysis. The pre-
processing began by converting the iEEG signals
to bipolar derivations by pairing adjacent elec-
trode contacts. Recording sites in the hippocam-
puswerepairedwithanearbywhite-matter
electrode that was identified anatomically using
FreeSurfer’ssegmentation( 68 ). We then resampled
each bipolar derivation at 500 Hz and removed
the 60-Hz power line interference (including its
harmonics) using zero-lag linear-phase Hamming-
windowed FIR band-stop filters (3 Hz wide).High-frequency broadband signal and
spectral analysis
HFB signal was defined in the present study
as the mean normalized power of frequenciesNormanet al.,Science 365 , eaax1030 (2019) 16 August 2019 10 of 14
RESEARCH | RESEARCH ARTICLE