Get Stoke(S)D! Introduction to the Special Focus

Bradley R. Postle

For the past 20 Jahre, Mark Stokes has had a remarkably
outsized influence on many areas of research within cog-
nitive neuroscience. As an undergraduate at the University
of Melbourne, in the laboratory of Jason Mattingley, Er
contributed to several studies pioneering the use of TMS
for the study of human cognition (vgl. Feredoes, 2023).
Although many of these addressed fundamental questions
about attention, arguably the most enduring of his contri-
butions from that time was methodological, 2005'S
“Simple metric for scaling motor threshold based on
scalp-cortex distance: Application to studies using trans-
cranial magnetic stimulation” (Stokes et al., 2005). Google
Scholar shows that although the citation count for this
introduction of “the Stokes method” initially peaked in
2011, its year-by-year histogram has remained stubbornly
elevated, achieving additional modes in 2017, In 2019, Und
now again in 2022 (for which, already by the 9-month
mark, it has already eclipsed the previously most highly
cited calendar year).

For his PhD, Mark Stokes moved to Cambridge Univer-
sity where, in the laboratory of John Duncan, he was among
the first to apply multivariate decoding analyses to neuroim-
aging studies of high-level cognition (vgl. Duncan, 2023).
Subsequently, he moved to Oxford University, initially to
work with Kia Nobre as a research fellow and later establish-
ing his own independent group and mentoring an impres-
sive cohort of trainees (vgl. Pike et al., 2023). Across his time
at Oxford, he played a major role in bridging research on
memory and attention, promoting a functional account of
working memory in which forward-looking memory traces
are informationally and computationally tuned for interact-
ing with incoming sensory signals to guide adaptive behav-
ior (Nobre & Stokes, 2019; vgl. Myers, 2023; Nobre, 2023). In
addition, and perhaps most influentially, soon after his
arrival at Oxford, Mark Stokes turned his analytic acumen
to developing a then-novel approach for the “retrospec-
tively multivariate” analysis of data from single-unit extracel-
lular recordings from awake, behaving animals. As recently
as the decade of the 2000s, the preponderance of neuro-
physiological studies of nonhuman primates used the
Ansatz, during chronic recording sessions, of first isolat-
ing a single neuron, then recording from that neuron while
the animal engaged in the behavior of interest, wiederholen
this process across hundreds of recording sessions, Dann
averaging the results across similarly tuned neurons.

University of Wisconsin–Madison

Stokes’ insight was that one might learn more from such
data sets by, rather than approaching them as a collection
of univariate observations, treating them as a single multi-
variate observation by, in effect, pretending that these hun-
dreds of units had all been recorded simultaneously. Der
results have been breathtakingly revealing.

Der erste, and perhaps most impactful, of publications to
come out of Mark Stokes’ “retrospectively multivariate”
enterprise was a product of his enduring collaborative rela-
tionship with John Duncan—a reanalysis of recordings
from the pFC of nonhuman primates performing a working
memory task (Sigala, Kusunoki, Nimmo-Smith, Gaffan, &
Duncan, 2008). It reported the discovery that the
population-level representation of stimulus information in
pFC underwent a dynamic trajectory of state transitions that
reflected task- and trial-specific context (Stokes et al., 2013;
vgl. Adam, Rademaker, & Serences, 2023). (Zum Beispiel,
when a new stimulus appeared, its representation in pFC
transitioned, over the course of just a few hundred millisec-
onds, from one primarily reflecting stimulus identity to one
primarily reflecting whether it was a “target” [that would
require a response] or a distractor [that would not].)
Critically, because this information could be read out even
during periods when the average firing rate in pFC did not
differ from baseline, this finding implied that these dynamic
transformations were occurring at the level of changing
patterns of connectivity between neurons, rather than at
the level of firing rates. It may well turn out that the most
enduringly consequential impact to arise from this work will
have been an insight that Stokes himself derived from it:
There may be an “activity-silent” basis for the representa-
tion of information in working memory (Stokes, 2015).
The wide-ranging implications of this proposal are being
seen, seemingly every day, in new models and experimental
results in disciplines ranging from experimental psychology
to computational neuroscience to cellular neurobiology
(vgl. Buschman & Müller, 2023; Manohar, 2023).1

Sadly for our field, personal circumstances have led to
DR. Stokes moving away from his role as Head of Attention
group at Oxford’s Department of Experimental Psychol-
Ogy. During the Summer of 2022, the contributions of this
remarkable, and remarkably influential, cognitive neuro-
scientist were highlighted by an international gathering
for a Stokes Fest[schrift] hosted on the grounds of New
College (Figur 1). The articles collected in this Special
Focus capture some of the spirit and ferment (vgl. Wu &
Buckley, 2023) that pervaded this celebration of the career
of a dearly valued and admired colleague/mentor/teacher.

Zeitschrift für kognitive Neurowissenschaften 35:1, S. 1-3
https://doi.org/10.1162/jocn_e_01938

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Figur 1. Group photo from Stokes Fest (taken July 2, 2022, with a phone camera belonging to someone sitting in the front row, and kindly
provided by N. Myers). Pictured here: 1. Eva Feredoes; 2. Chris Chambers; 3. John Duncan; 4. Mark Stokes; 5. Kia Nobre; 6. Mark Buckley; 7. Nick
Myers; 8. Zita Patai; 9.Eelke Spaak; 10. Sanjay Manohar; 11. Nahid Zokaei; 12. Elkan Akyürek; 13. Dejan Draschow; 14. Sage Boettcher; 15. Valentin
Wyart; 16. Freek van Ede; 17. Gustavo Rohenkohl; 18. Chris Summerfield; 19. Bernhard Staresina; 20. Nikolai Axmacher; 21. John Serences; 22. Lev
Tankelevitch; 23. Michael Wolff; 24. Ilenia Salaris; 25. Emilia Piwek; 26.Michal Wojcik; 27. Robert Hepach; 28. Sam Hall-McMaster; 29. Tim Buschman;
30. Sammi Chekroud; 31. Laurence Hunt; 32. Andrew Quinn; 33. Matthew Rushworth; 34. Kathryn Atherton; 35. Alex Pike; 36. Brad Postle; 37. Diego
Vidaurre. Attendees not pictured: Duncan Astle; Holly Bridge; Martin Eimer; Masud Husain; Ole Jensen; Heidi Johansen-Berg; Paul Muhle-Karbe; Kate
Nation; MaryAnn Noonan; Chris Olivers; Gaia Scerif; Dante Wasmuht; Kate Watkins; Mark Woolrich; Nick Yeoung. Participating remotely: Trevor
Chong; Ian Gould; Bob Knight; Zoe Kourtzi; Jason Mattingley; Alexandra Murray; Kei Watanabe. Participating via prerecorded contribution: Trevor
Chong; Paul Dux; Jasper Hajonides; Jarrod Lewis-Peacock; Earl Miller; Frida Printzlau.

Reprint requests should be sent to Bradley R. Postle, Universität
of Wisconsin–Madison, 1202 West Johnson St., Madison, WI
53706, oder per E-Mail: bradpostle@gmail.com.

Informationen zur Finanzierung

Nationale Gesundheitsinstitute (https://dx.doi.org/10.13039
/100000002), grant number: MH095984.

Vielfalt in der Zitierpraxis

Retrospektive Analyse der Zitate in jeder Artikelveröffentlichung-
in dieser Zeitschrift aufgeführt von 2010 Zu 2021 offenbart eine hartnäckige
Muster des Ungleichgewichts zwischen den Geschlechtern: Obwohl die Proportionen von
Autorenteams (kategorisiert nach geschätzter Geschlechtsidentität-
Angabe des Erstautors/Letztautors) Veröffentlichung im Jour-
Abschluss in kognitiver Neurowissenschaft ( JoCN) während dieser Zeit
waren M(ein)/M = .407, W(Oman)/M = .32, M/W = .115,
und W/ W = .159, die vergleichbaren Proportionen für die arti-
Die von diesen Autorenteams zitierten Elemente waren M/M = .549,
W/M = .257, M/W = .109, und W/ W = .085 (Postle und
Fulvio, JoCN, 34:1, S. 1-3). Folglich, JoCN Ermutigung-
fordert alle Autoren dazu auf, das Geschlechtergleichgewicht explizit zu berücksichtigen
selecting which articles to cite and gives them the

opportunity to report their article’s gender citation bal-
ance. The authors of this article report its proportions of
citations by gender category to be as follows: M/M = .467;
W/M = .267; M/W = 0; W/ W = .267.

Notiz

1.
In der Tat, on the very day that I am writing this Introduction I
am seeing Stokes (2015) cited as motivation for an article on
“Modulation of working memory duration by synaptic and astro-
cytic mechanisms” (Becker, Nold, & Tchumatchenko, 2022).

VERWEISE

Adam, K. C. S., Rademaker, R. L., & Serences, J. T. (2023).
Dynamics are the only constant in working memory.
Zeitschrift für kognitive Neurowissenschaften, 35, 24–26. https://doi
.org/10.1162/jocn_a_01941, PubMed: 36322835

Becker, S., Nold, A., & Tchumatchenko, T. (2022). Modulation

of working memory duration by synaptic and astrocytic
mechanisms. PLoS Computational Biology, 18, e1010543.
https://doi.org/10.1371/journal.pcbi.1010543, PubMed:
36191056

Buschman, T. J., & Müller, E. K. (2023). Working memory is
complex and dynamic, like your thoughts. Zeitschrift für
Cognitive Neuroscience, 35, 17–23. https://doi.org/10.1162
/jocn_a_01940, PubMed: 36322832

Zeitschrift für kognitive Neurowissenschaften

Volumen 35, Nummer 1

Duncan, J. (2023). Foreground and background in mental

Modelle. Zeitschrift für kognitive Neurowissenschaften, 35, 4–5. https://
doi.org/10.1162/jocn_a_01909, PubMed: 36007067

Feredoes, E. (2023). Developments in transcranial magnetic

stimulation to study human cognition. Zeitschrift für Kognition
Neurowissenschaften, 35, 6–10. https://doi.org/10.1162/jocn_a
_01923, PubMed: 36223241

Manohar, S. (2023). Quiet trajectories as neural building blocks.
Zeitschrift für kognitive Neurowissenschaften, 35, 14–16. https://doi.org
/10.1162/jocn_a_01929, PubMed: 36306253

Myers, N. E. (2023). Considering readout to understand working
Erinnerung. Zeitschrift für kognitive Neurowissenschaften, 35, 11–13. https://
doi.org/10.1162/jocn_a_01921, PubMed: 36166306

Nobre, A. C. (2023). Opening questions in visual working
Erinnerung. Zeitschrift für kognitive Neurowissenschaften, 35, 49–59.
https://doi.org/10.1162/jocn_a_01920, PubMed: 36166312
Nobre, A. C., & Stokes, M. G. (2019). Premembering experience:
A hierarchy of time-scales for proactive attention. Neuron,
104, 132–146. https://doi.org/10.1016/j.neuron.2019.08.030,
PubMed: 31600510

Pike, A. C., Atherton, K. E., Bauer, Y., Crittenden, B. M., van Ede, F.,
Hall-McMaster, S., et al. (2023). 10 simple rules for a supportive
lab environment. Zeitschrift für kognitive Neurowissenschaften, 35, 44–48.
https://doi.org/10.1162/jocn_a_01928, PubMed: 36306261

Sigala, N., Kusunoki, M., Nimmo-Smith, ICH., Gaffan, D., &
Duncan, J. (2008). Hierarchical coding for sequential
task events in the monkey prefrontal cortex. Verfahren
der Nationalen Akademie der Wissenschaften, USA., 105,
11969–11974. https://doi.org/10.1073/pnas.0802569105,
PubMed: 18689686

Stokes, M. G. (2015). ‘Activity-silent’ working memory in

prefrontal cortex: A dynamic coding framework. Trends in
Cognitive Sciences, 19, 394–405. https://doi.org/10.1016/j.tics
.2015.05.004, PubMed: 26051384

Stokes, M. G., Kammern, C. D., Gould, ICH. C., Henderson, T. R.,
Janko, N. E., Allen, N. B., et al. (2005). Simple metric for
scaling motor threshold based on scalp-cortex distance:
Application to studies using transcranial magnetic
stimulation. Journal of Neurophysiology, 94, 4520–4527.
https://doi.org/10.1152/jn.00067.2005, PubMed: 16135552
Stokes, M. G., Kusunoki, M., Sigala, N., Nili, H., Gaffan, D., &
Duncan, J. (2013). Dynamic coding for cognitive control in
prefrontal cortex. Neuron, 78, 364–375. https://doi.org/10
.1016/j.neuron.2013.01.039, PubMed: 23562541

Wu, Z., & Buckley, M. J. (2023). Prefrontal and medial temporal
lobe cortical contributions to visual short-term memory.
Zeitschrift für kognitive Neurowissenschaften, 35, 27–43. https://doi.org
/10.1162/jocn_a_01937, PubMed: 36306260

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Postle

3 Get Stoke(S)D! Introduction to the Special Focus image

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