Erratum: Different forms of effective connectivity in primate frontotemporal pathways

Abstract

It is generally held that non-primary sensory regions of the brain have a strong impact on frontal cortex. However, the effective connectivity of pathways to frontal cortex is poorly understood. Here we microstimulate sites in the superior temporal and ventral frontal cortex of monkeys and use functional magnetic resonance imaging to evaluate the functional activity resulting from the stimulation of interconnected regions. Surprisingly, we find that, although certain earlier stages of auditory cortical processing can strongly activate frontal cortex, downstream auditory regions, such as voice-sensitive cortex, appear to functionally engage primarily an ipsilateral temporal lobe network. Stimulating other sites within this activated temporal lobe network shows strong activation of frontal cortex. The results indicate that the relative stage of sensory processing does not predict the level of functional access to the frontal lobes. Rather, certain brain regions engage local networks, only parts of which have a strong functional impact on frontal cortex.

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ARTICLE
Received 28 May 2014 |Accepted 28 Nov 2014 |Published 23 Jan 2015
Different forms of effective connectivity in
primate frontotemporal pathways
Christopher I. Petkov1,2, Yukiko Kikuchi1,3,4, Alice E. Milne1, Mortimer Mishkin3,
Josef P. Rauschecker4,6 & Nikos K. Logothetis2,5
It is generally held that non-primary sensory regions of the brain have a strong impact on
frontal cortex. However, the effective connectivity of pathways to frontal cortex is poorly
understood. Here we microstimulate sites in the superior temporal and ventral frontal cortex
of monkeys and use functional magnetic resonance imaging to evaluate the functional activity
resulting from the stimulation of interconnected regions. Surprisingly, we find that, although
certain earlier stages of auditory cortical processing can strongly activate frontal cortex,
downstream auditory regions, such as voice-sensitive cortex, appear to functionally engage
primarily an ipsilateral temporal lobe network. Stimulating other sites within this activated
temporal lobe network shows strong activation of frontal cortex. The results indicate that the
relative stage of sensory processing does not predict the level of functional access to the
frontal lobes. Rather, certain brain regions engage local networks, only parts of which have a
strong functional impact on frontal cortex.
DOI: 10.1038/ncomms7000 OPEN
1Institute of Neuroscience, Framlington Place, Newcastle University, Newcastle upon Tyne NE2 4HH, UK. 2Department of Physiology of Cognitive Processes,
Max Planck Institute for Biological Cybernetics, 38 Spemannstrasse, 72076 Tu
¨bingen, Germany. 3Laboratory of Neuropsychology, NIMH, NIH, 31 Center
Drive, Bethesda, Maryland 20892, USA. 4Department of Neuroscience, Georgetown University Medical Center, 3970 Reservoir Road, N.W., Washington,
District of Columbia 20057, USA. 5Division of Imaging Science and Biomedical Engineering, University of Manchester, Stopford Building, Oxford Road,
Manchester M13 9PT, UK. 6Institute for Advanced Study, Technische Universita
¨tMu
¨nchen, Lichtenbergstrasse 2a, Garching 85748, Germany.
Correspondence and requests for materials should be addressed to C.I.P. (email: chris.petkov@ncl.ac.uk).
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There is considerable interest in understanding the func-
tional connectivity of the brain, including pathways to
frontal cortex that enable communication1–3. Primary
cortical areas, which are the sensory input recipients of the
neocortex, are not as strongly interconnected with frontal cortex
as are non-primary sensory and association areas4–8. Thereby, the
generally held notion is that certain processing stages, by virtue of
their position, have privileged access to frontal cortex. However,
although there is substantial evidence that the brain processes
information both in serial and parallel7,9, it is less clear whether
there is a principal form of arrangement10,11. Since the effective
functional connectivity of the brain is poorly understood, it
remains possible that certain sensory processing stages, regardless
of their position, are effective in engaging frontal cortex by
themselves or interact with other regions to indirectly gain
functional access to frontal cortex.
In the auditory system, primary auditory cortex has a local
interconnectivity pattern, where neuronal connectivity is stronger
between adjacent than non-adjacent cortical areas12. However,
structures as early as the second stage of auditory cortical
processing show direct projections to frontal cortex. Notably,
tracer injections into the lateral auditory belt9,10 mono-
synaptically label axonal boutons in either ventral or dorsal
frontal cortex5, depending on whether the injections are made in
ventral or dorsal parts of the auditory belt5. These observations
are consistent with the guiding notion of parallel processing
pathways to frontal cortex1,13, where ventral and dorsal streams
process object features and spatial content, respectively.
Downstream from the auditory belt are anatomical areas
Ts1/Ts2 (ref. 14), which represent the fourth or fifth
anatomically defined stage of processing (Fig. 1a). This
anterior/ventral temporal lobe region is known in humans15
and macaque monkeys16 to contain clusters of neurons17
sensitive to voice content in communication sounds, such as
the acoustical features associated with voice identity, that is, ‘who’
vocalized. The functional characteristics of voice-sensitive
neurons (which in macaques are located in the anterior
supratemporal plane, aSTP; Fig. 1a) differ from those of
neurons in the adjacent multisensory association cortex, in the
upper bank of the anterior superior temporal sulcus (aSTS).
Namely, aSTP neurons are more auditory feature sensitive and
show less specific multisensory responses than neurons in the
aSTS18; also see refs 19–21.
Given that the auditory belt projects to frontal cortex, one
might expect neurons in aSTP areas Ts1/Ts2 to do the same.
However, this remains unresolved. A number of earlier studies
injecting anterograde tracers into Ts1/Ts2 report strong labelling
in frontal cortex, but these studies also intended to make their
tracer injections large enough to involve adjacent association
cortex on the gyrus and aSTS, which is known to project to
frontal cortex6,22,23. Others studying retrograde projections
from ventral, orbital or medial frontal cortex to Ts1/Ts2 (or
RTp by other nomenclature24) show a divergence of results, with
some reporting strong8,25,26 and others negligible27,28 labelling.
Nonetheless, some synapses could be more effective than others,
and it has been difficult to address the direction of effective
connectivity with the available neuroimaging approaches4,29.
Therefore, the key question is: would a downstream sensory
processing stage, such as voice-identity sensitive cortex in the
aSTP, directly engage ventral frontal and orbital frontal cortex or
would it interact with a local temporal lobe network to gain
functional access to frontal cortex?
To tackle this question, we combined microstimulation and
functional magnetic resonance imaging (fMRI) in rhesus
macaques30–35. Neuronal microstimulation of a given cortical
site elicits an fMRI response in interconnected regions but
appears to be prevented from propagating loosely throughout the
cortex by intracortical inhibition in the target regions30. In this
case, it is possible that combined microstimulation and fMRI
could be useful for charting the effective connectivity of a
neuronal network, whereby after microstimulating a site and
using fMRI to identify its activated targets, one of the
demonstrated target sites could then be stimulated to reveal
which additional areas become activated. Alternatively, in the case
of less selective effects of combined microstimulation, one
might expect stimulation of two adjacent regions to show
indistinguishable fMRI activity patterns. Figure 1b,c illustrates
Hypothesis 2: aSTP also activates frontal cortex
Auditory cortical hierarchy (neuroanatomically defined)
Dorsal
Anterior
A1
Ts2
Ts1
Tpt
Rostral
parabelt
Caudal
parabelt
CM
R
RT
CL
Frontal
cortex
Temporal lobe
aSTP
aSTP
aSTS
Sagittal
Temporal Lobe
aSTP
aSTS
Hypothesis 1: aSTP mainly activates temporal lobe
OFC
OFC
MPFC
Frontal
pole
Lateral
sulcus
Auditory
lateral belt
Temporal lobe
aSTS
OFC
OFC
VLPFC
Frontal
pole
Lateral
sulcus
Auditory
lateral belt
DLPFC
MM
RM
RTM ML
AL
RTL
Prim aud. ctx. (core)
Belt
Parabelt
Downstream auditory
Anterior belt
aSTP
Caudal belt
aSTS
Stimulation sites:
Anterior belt
aSTP
Caudal belt
aSTS
Stimulation sites:
VLPFC
DLPFC
MPFC
Auditory cortical fields
P
D
A
V
A
D
P
V
Lateral
Medial
aSTP
Figure 1 | Auditory cortical processing stages and illustrated hypotheses.
(a) Schematic of the known macaque auditory cortical hierarchy. For the
definition of abbreviations for the different auditory cortical fields, see
ref. 49. More ventral to these auditory regions (in the upper bank of the
superior temporal sulcus, STS) are multisensory regions and further ventral
(in the fundus and lower bank of the STS) are visual areas. (b,c) Illustrated
hypotheses of aSTP effective connectivity. (b) Hypothesis 1 illustrates that
stimulation of aSTP (red arrows) results mainly in anterior temporal lobe
activity. (c) Hypothesis 2 illustrates that aSTP stimulation (red arrows) also
activates orbital/medial frontal cortex (OFC/MPFC). Note that stimulation
of other brain areas such as the lateral belt can help to evaluate to what
extent combined microstimulation and fMRI recapitulates key findings from
neuronal tractography studies. Thereby, in both hypotheses, we illustrate
findings that could be consistent with neuronal tractography results, such
as: ventrolateral prefrontal cortex (VLPFC) projections from anterior lateral
belt fields5,25 in blue arrows and dorsolateral prefrontal cortex (DLPFC)
projections from caudal lateral belt fields5,25 in green arrows; also shown in
yellow arrows are aSTS projections to OFC or medial prefrontal cortex
(MPFC)8,27; see text for further details.
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two alternative hypotheses. In one case, aSTP stimulation mainly
results in temporal lobe activity, whereas aSTS stimulation leads
to additional frontal activation (Fig. 1b). Alternatively,
stimulating the aSTP results in ventral and orbital/medial
frontal activity that cannot be distinguished from that of
stimulating the aSTS (which is known to project to orbital/
medial frontal cortex8,23,27; see Fig. 1c). Note that in both cases,
control experiments are needed to clarify the extent to which
microstimulation and fMRI is consistent with established
anterograde neuronal tractography results. This is illustrated in
both Fig. 1b,c as anterior lateral belt fields projecting to ventral
frontal cortex and more caudal lateral belt fields projecting to
more dorsal parts of lateral frontal cortex5,25,36. Testing these
hypotheses could reveal how auditory temporal lobe regions are
connected with frontal cortex, and, with the auditory system as a
model, our study could clarify whether there might be other
exceptions to a principal form of cortical arrangement besides
those coming from the visual system7,10,11.
Here we microstimulate fMRI-identified voice-sensitive clusters,
localized to the aSTP and observe an fMRI response restricted to
the ipsilateral anterior temporal lobe. By contrast, on stimulating
another site within this activated network, a region in the aSTS, we
additionally observe strong orbital frontal activation. Further
experiments stimulating different parts of the auditory belt and
the ventral frontal cortex confirm key prior neuronal anterograde
tractography findings, clarifying the interpretation of the aSTP
stimulation results. We provide evidence for different forms of
effective connectivity in primate auditory temporal to frontal
pathways, showing that certain non-primary auditory regions, like
the voice-identity sensitive cortex in the aSTP, appear to rely on
adjacent temporal lobe processes before gaining access to frontal
cortex. This finding is in stark contrast to the results obtained by
stimulating the auditory lateral belt and aSTS sites. Together the
results raise the possibility that the auditory stage of processing
does not predict the level of engagement of the frontal cortex.
Results
fMRI localizer results and microstimulation approach. In four
rhesus macaques, we first used fMRI and sounds varying in fre-
quency to localize the tonotopically organized auditory core and
belt fields37. We also used fMRI to localize voice-sensitive clusters
in the aSTP(in anatomical areas Ts1/Ts2 (refs 14,16)). This region
is anterior to the tonotopically organized auditory core (primary)
and belt (secondary) fields and is known to be voice-identity
sensitive16 (Fig. 2, Supplementary Figs 1–4). FMRI voice-area
localization was conducted using voice versus non-voice or voice-
identity adaptation experiments16. Our hypotheses focus on the
Ts1/Ts2 regions; thus, voice-sensitive clusters were analysed only
within these regions, although it is known that there are other
voice-sensitive clusters in the human15 and macaque16 brain.
Given the large number of localizers and experiments conducted
here, all the fMRI localizer and microstimulation experiments
were conducted under anaesthesia using an established protocol.
The results from using this protocol have previously been
compared and noted to be largely comparable to those obtained
in awake animals16,30,31,37–39 (also see Supplementary Text and
Discussion).
Voice-sensitive clusters in the aSTP were observed in the left or
both hemispheres of the four study animals (Fig. 2,
Supplementary Figs 1–4). This result is consistent with previous
observations of a lack of significant lateralization of monkey voice
clusters16. The first monkey (M1) had bilaterally distributed
anterior voice-sensitive clusters (Supplementary Figs 1,5).
Thus, in this animal, we implanted chambers over both
hemispheres and compared the results of stimulating left- and
right-hemisphere sites. We noted no qualitative hemispheric
differences in several of the key findings reported here
(Supplementary Fig. 5). Thus, the remaining animals (M2–4)
were implanted with left-hemisphere chambers for consistency.
In targeting fMRI-identified sites for microstimulation, we used
the coordinates from the fMRI voice or tonotopy localizers. For
structural MRI-identified sites, we used the coordinates of the
MRI structural scans, which were referenced to a rhesus macaque
brain atlas in stereotactic coordinates24. As the electrode was
advanced to the target region, it generated a local MRI signal
dropout, such that its general location could be identified in
structural scans (Fig. 2 and Supplementary Figs 1–6). For greater
targeting precision, as we slowly approached the target site, we
monitored neuronal spiking activity relative to the
neurophysiologically ‘quiet’ transition areas, such as the lateral
sulcus above the aSTP or the white matter between the aSTP and
aSTS. This allowed us to advance the electrode to be B1mm
within the grey matter of the target site.
Effects of microstimulating aSTP and aSTS sites. Micro-
stimulation of both aSTP and aSTS sites was successful in three
out of the four macaques studied (M1–3). In the fourth macaque
…
0 0.2 0.6
Time (s)
200 Hz
03
Time (s)
15
fMRI voice-area localizer
and microstimulation sites
ON
0
1
2
fMRI
signal change (%)
Microstimulation paradigm
biphasic pulses (0.2 ms)
OFF
18
aSTS site
Stimulating
electrode
tract
aSTP site
…
Superior
temporal
sulcus (STS)
Lateral sulcus
Figure 2 | Anterior superior temporal regions targeted for
microstimulation and the approach. (a) illustrates the left hemisphere
approach (in monkey 1, M1) for targeting either the anterior voice-sensitive
cluster, localized to the aSTP (in fields Ts1/Ts2 on the plane), or a more
ventral site in the upper bank of the aSTS (in field TPO24). The aSTP voice-
sensitive cluster (in red) is based on a separately obtained voice versus
non-voice fMRI localizer (see Supplementary Figs 1–4 for additional
examples). The position of the electrode can be identified by its local signal
dropout (see text for further details). (b) Schematic of the microstimulation
paradigm showing periods of biphasic stimulation alternating with no-
stimulation periods. (c) Illustrative time course of the fMRI BOLD signal in
the aSTS in response to stimulation of the aSTP (from the experiment
shown in Fig. 3a).
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(M4), the results from stimulating the aSTS were consistent with
those from the other three macaques (Supplementary Fig. 7).
However, stimulating the aSTP site in M4 did not result in sig-
nificantly activated voxels anywhere in the brain (cluster cor-
rected Po0.05). Therefore, only the aSTP and aSTS results
available from M1–3 could be analytically compared and analysed
further.
Microstimulation of the aSTP site in the three animals (M1–3;
Figs 3–5) resulted in significant (cluster corrected Po0.05) fMRI
blood oxygen level dependant (BOLD) responses from a number
of regions, largely restricted to the ipsilateral anterior temporal
lobe (Figs 3–5a). Notably, no significant contralateral (right)
hemisphere activity was observed in any of the animals. The
activated anatomical areas in common across the three animals,
resulting from aSTP microstimulation, involved the aSTS,
temporopolar cortex and anterior auditory cortical fields (ACFs;
see Supplementary Fig. 8). Supplementary Tables 1–3 summarize
the significantly activated anatomical areas seen in each animal.
In two out of these three animals’ results, the following additional
areas in the ipsilateral anterior temporal lobe and operculum were
activated in common: visual area TE, agranular insula in the
temporal operculum and area PrCO in the frontal operculum.
Notably, there was no clear functional engagement of orbital,
medial, dorsal or ventral frontal cortex.
Thereby, the results from microstimulating the voice-sensitive
cluster in the aSTP showed clear functional activation of an
anterior temporal network (including the aSTS) but not of the
frontal cortex, barring area PrCO in the frontal operculum that
was observed in the majority of stimulation cases. Because such a
result may be due to the inherent limitations of direct electrical
stimulation (DES)40 rather than to interarea connectivity, we
tested whether stimulation of a target region within the observed
activated local network would activate frontal cortex more
strongly. We selected an aSTS site that we had observed was
consistently activated by stimulating the aSTP (Figs 3–5a).
Microstimulating the aSTS resulted in a significant activity
0
1
2
ROI mean voxel
z-score
***
aSTS site 2
Dorsal
Anterior
stimulating
electrode
tract
aSTP site 1
n = 75 stim trials
n = 75 stim trials
5 mm
Left lateral
Left aSTP microstimulation
Monkey 1
Left medial
Left aSTS microstimulation
OFC
OFC
A
D
P
V
A
D
P
V
aSTS
aSTP
aSTS vs aSTP contrast difference
aSTS
aSTP
z-score 152.3
p-value
cluster corrected
10–48
0.05
p-value uncor.
aSTS z-score difference aSTP
15 3.3 3.3 15
10–48 0.001 0.001 10–48
aSTS
aSTP
aSTSaSTP
OFC
Figure 3 | Comparison of the effects of aSTP and aSTS stimulation in
Monkey 1. (a) Significantly activated clusters (cluster corrected Po0.05) in
Macaque 1 (M1) resulting from stimulating the voice-sensitive cluster in the
aSTP (Supplementary Fig. 1; crosshairs identify site of stimulation). Results
are shown on a surface-rendered macaque template brain (gyri, light grey;
sulci, dark grey). (b) Significantly activated clusters resulting from aSTS
microstimulation. (c) Analytical contrast between the effects of stimulating
the aSTS versus aSTP sites. Bar graphs show the results of anatomically
defined ROI analyses (shown is the ROI mean voxel zscore, ±s.e.m.,
across trials). The results show that the OFC ROI is consistently more
activated by aSTS than by aSTP stimulation (Supplementary Table 1
summarizes the anatomical regions activated). No significantly activated
voxels were observed in the contralateral (right) hemisphere.
D
V
PA
Left lateral
Left medial
Left aSTP microstimulation
Left aSTS microstimulation
aSTS vs aSTP contrast difference
D
V
AP
2.3 15
0.05 10–48
Monkey 2
aSTS
aSTS
0
0.6
1.2
ROI mean voxel
z score
***
15
10–48
3.315
0.001
10–48 0.001
3.3
OFC
aSTP
aSTP
5 mm
n = 24 stim trials
n = 24 stim trials
OFC
OFC
aSTP
aSTS
aSTS aSTP
aSTSaSTP
z score
P value
cluster corrected
z score difference
P value uncor.
Figure 4 | Comparison of the effects of aSTP and aSTS stimulation in
Monkey 2. Shown are the significantly activated clusters (cluster corrected
Po0.05) in Macaque 2 (M2) resulting from stimulating the voice-sensitive
aSTP (a) or the aSTS (b). (c) Analytical contrast between the effects of
stimulating the aSTS versus aSTP sites. Format as in Fig. 3. No significantly
activated voxels were observed in the contralateral (right) hemisphere. See
manuscript Supplementary Table 2 for a summary of the significantly
activated anatomical regions.
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response in a comparable ipsilateral anterior temporal lobe
network, as seen by stimulating the aSTP. In sharp contrast,
however, aSTS microstimulation prominently activated the
orbital frontal cortex (OFC; Figs 3–5b; Supplementary
Tables 1–3). The following anatomical areas were signi-
ficantly activated in common in M1–3: adjacent aSTS regions,
temporopolar cortex, anterior ACFs, visual area TE, hippocampus
and entorhinal cortex and notably the orbital frontal cortex (area
13). In two of the three animals the additionally activated areas
included the amygdala, agranular insula and the frontal
operculum (area PrCo). Other results recapitulated these main
observations and confirmed the reliability of the findings: See the
further replication experiments from stimulating the left and right
aSTP in M1 (Supplementary Figs 5 and 8), the right aSTP and
aSTS in M1 (Supplementary Fig. 6) and stimulating the left aSTS
in M4 (Supplementary Fig. 7).
For a more direct comparison between the effects of
stimulating aSTS versus aSTP, we next analytically contrasted
these results and also performed planned region-of-interest (ROI)
analyses. The analytical comparison of aSTS versus aSTP in M1–3
showed significantly greater activity in the ipsilateral orbital
frontal cortex and certain anterior temporal lobe sites, such as
visual area TE (Figs 3–5c; thresholded at Po0.001 for consistency
across the animals, see Methods; also see Supplementary
Tables 1–3 for cluster voxel numbers and peak voxel zscores).
Furthermore, an anatomically defined ROI analysis confirmed the
stronger OFC activation by aSTS stimulation in the three animals
(all results Po0.001; bar graphs in Figs 3–5c). We then combined
the three monkeys’ results into a mixed-effects analysis of
variance (ANOVA), with ‘monkey’ as a random between-subjects
factor and ‘site’ of stimulation (aSTS or aSTP) as a within-subjects
fixed factor. The result of this analysis recapitulated that
stimulating the aSTS elicited greater activity in the OFC ROI
than that produced by aSTP stimulation (F
1,752
¼20.4, P¼0.045).
There was no significant effect of the monkey factor or
interaction between the factors. When hemisphere was added to
the model a significant effect of hemisphere was observed
(F
1,1964
¼62.81, P¼0.015), confirming that the results were
lateralized to the stimulated ipsilateral hemisphere. As a point of
reference, analysing the effect of site of stimulation in an anterior
auditory cortex ROI (consisting of anterior auditory core and belt
areas24) showed no consistent effect of site of stimulation in the
animals individually (Supplementary Fig. 9), suggesting that no
over or underactivation of the anterior auditory cortex occurs
with either aSTS or aSTP stimulation. This observation was
recapitulated by conducting the combined animal ANOVA with
the voxel-based responses from the anterior auditory cortex ROI,
which showed no significant differences between aSTS or aSTP
stimulation in the activation of anterior auditory core and belt
areas.
In summary, the results showed greater OFC activation from
the stimulation of the aSTS than from the stimulation of the
aSTP. The aSTP stimulation did not strongly activate any frontal
region, excepting the frontal operculum (area PrCO), which
stimulation of either aSTP or aSTS could activate in the majority
of cases. Both stimulation sites also resulted in strong ipsilateral
activity involving the anterior temporal lobe. This reveals a
common functional network, with the key difference that
stimulating the aSTS (anatomical area TPO) resulted in orbital
frontal activation. To understand these results in a broader
context, we conducted further experiments in two of the
macaques (M3–4) stimulating different sites in fMRI-identified
tonotopically organized auditory belt fields and separately also in
the ventral frontal cortex.
Microstimulation of auditory belt fields. Romanski et al.5,36
injected anterograde tracers in the ventral/anterior and dorsal/
caudal lateral belt (auditory cortical fields: AL and CL,
respectively). They obtained results consistent with a dual
pathways model1,13 and evidence that neurons as early as those
in the belt, the second key stage of auditory cortical processing,
project to frontal cortex36. They also noted that caudal auditory
belt regions project to more dorsal regions in the lateral frontal
cortex, whereas the more anterior regions in auditory cortex
target ventral regions in the lateral and orbital frontal cortex5,36.
Using fMRI tonotopic mapping37 we targeted for
microstimulation field RTL, the most anterior lateral belt field
situated in front of AL (Fig. 6). In another experiment, the
placement of the chamber enabled targeting of ML, a mid/caudal
lateral belt field (Fig. 7). Overall, our microstimulation results
were complementary to those obtained by neuronal tractography
studies5,41. First, unlike the results from stimulating aSTP and
aSTS (Figs 3–5), stimulating these auditory belt fields resulted in
D
V
PA
Left lateral
Left aSTP microstimulation
Left aSTS microstimulation
aSTS vs aSTP contrast difference
2.3 15
0.05 10–48
Monkey 3
0
0.7
1.4
ROI mean voxel
z score
***
aSTS
aSTS
OFC
aSTP
aSTP
5 mm
n = 90 stim trials
n = 90 stim trials
OFC
OFC
aSTP
aSTS
aSTS aSTP
aSTS
aSTP
15
10–48
3.315
0.00110–48 0.001
3.3
D
V
AP
Left medial
z score
P value
cluster corrected
z score difference
P value uncor.
Figure 5 | Comparison of the effects of aSTP and aSTS stimulation in
Monkey 3. Shown are the significantly activated clusters (cluster corrected
Po0.05) in Macaque 3 (M3) resulting from stimulating the voice-sensitive
aSTP (a) or the aSTS (b). (c) Analytical contrast between the effects of
stimulating the aSTS versus aSTP sites. Format as in Fig. 3. No significantly
activated voxels were observed in the contralateral (right) hemisphere. See
manuscript Supplementary Table 3 for a summary of the significantly
activated anatomical regions.
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significant (cluster corrected Po0.05) cross-hemisphere
activation (including activation of homotopic auditory cortical
fields in the opposite hemisphere; Supplementary Tables 4 and 5;
Figs 6 and 7). This observation is consistent with the reported
transcallosal tractography of auditory cortex41. Second,
stimulating the auditory lateral belt resulted in strong frontal
cortex activity. In the case of stimulating the mid/caudal belt field
ML, activation was seen in more dorsal frontal areas 46 and area 8
(Fig. 7, Supplementary Table 5), which is generally consistent
with the reported anterograde projection to frontal cortex of
caudal belt field CL5,36. By comparison, stimulating the anterior
belt field RTL resulted in more ventral frontal and orbital frontal
(area 13) activity (Fig. 6, Supplementary Table 4), which is
consistent with the projection pattern to frontal cortex of the
anterior belt field AL5,36. Thus, the results from electrically
stimulating lateral auditory belt fields correspond in a number of
ways to the key findings from neuronal tracing studies, further
underscoring the very different pattern of results seen from
stimulating the aSTP and aSTS.
Microstimulation of sites in ventral frontal cortex. A number of
neuroanatomical studies have examined connections between
frontal and temporal cortex5,6,8,22,23,25,27,42. The general
observations from these studies is that dorsal parts of the frontal
cortex interconnect with dorsal frontal, parietal and temporal areas,
whereas more ventral frontal cortical areas are interconnected with
ventral/anterior areas using ventral pathways such as the uncinate
fasciculus or extreme capsule. In M3–4, we stimulated three areas
in the ventral frontal cortex, differing along the dorsoventral axis
(Figs 8–10). The results are consistent with the evidence that more
dorsal parts of ventral frontal cortex are interconnected with more
dorsal regions of the brain (Fig. 8). Specifically, stimulating the
more dorsal of these frontal sites (area 45) produced the clearest
contralateral engagement in these three experiments and resulted
in significant activation (cluster corrected Po0.05) of relatively
more dorsal regions such as areas 6, 8, 9 and 4 (Fig. 8;
Supplementary Table 6). By contrast, stimulating a more ventral
site in area 6va or area F5 resulted in more ventral regions being
significantly activated, which included the frontal operculum, area
44/45, STS and auditory belt/parabelt. In this case, no significant
activation is seen in dorsolateral frontal regions or in aSTP fields
Ts1/Ts2 (Fig. 9, Supplementary Table 7). Stimulating the most
ventral site (of the three shown in Fig. 10) within the operculum,
near the border of the agranular and dysgranular insula, resulted in
a strong activation of the anterior temporal lobe (including aSTP
areas Ts1/Ts2 and the aSTS) and the adjacent orbital frontal cortex,
among other ventral regions (Supplementary Table 8).
Left lateral Right lateral
Left anterior auditory cortex (belt field RTL) microstimulation (M4)
5 mm
2.3 15
0.05 10–48
Dorsal
Anterior
aSTP
aSTS
n = 30 stim trials
Targeting lateral anterior
auditory belt field (RTL)
A1
CM
R
ML
AL
RTL
CL
A1
RTL
right
Anterior
Axial
Sagittal
Right medialLeft medial
z score
P value
Cluster corrected
Figure 6 | fMRI results from stimulating an anterior lateral belt field. Top left panels show the tonotopically organized auditory core and belt fields,
which were localized separately using fMRI activity in response to tones and band-passed noise varying in frequency37. Bottom panels show the
result of microstimulating the anterior lateral belt field RTL. Note the prominent cross-hemisphere activation and significant activation of orbitofrontal and
ventrolateral frontal cortex. Supplementary Table 4 summarizes the anatomically activated regions resulting from stimulation of this region in the
lateral belt.
ML
ML
Sagittal
n = 75 stim trials
A1
CM
R
AL
RTL
CL
Targeting lateral mid/caudal
auditory belt field (ML)
A1
D
V
PA
D
V
A
P
Right lateral
D
V
AP
D
V
PA 5 mm
2.3 15
0.05 10–48
Dorsal
Anterior
Right medial
Left medial
aSTP
aSTS
z score
P value
Cluster corrected
Left mid/caudal auditory cortex (belt field ML) microstimulation (M3)
Left lateral
Figure 7 | fMRI results from stimulating a mid/caudal lateral belt field. Format as in Fig. 6. Top left panels show the tonotopically organized auditory core
and belt fields37. Bottom panels show the result of microstimulating the mid/caudal lateral belt field ML. Note the prominent cross-hemisphere activation
and significant activation of ventral and dorsolateral frontal cortex. Supplementary Table 5 summarizes the anatomically activated regions resulting from
stimulating this region in the lateral belt.
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Left lateral
Right medial
Left medial
Left VPFC (area 6va/F5) microstimulation (M3)
D
V
AP
V
AP
D
V
PA
D
V
PA
2.3 15
0.05 10–48
VLPFC
FOP STP
n = 75 stim trials
xyz = –21,30,12
6va/F5
site
6va/F5
site
Electrode tract
z score
P value
cluster corrected
Right lateral
D
Figure 9 | fMRI results from microstimulating frontal cortex area 6va/F5. Format as in Fig. 8. Top right panels show the electrode position and targeting
approach for this experiment. Bottom panels show the results from stimulating area 6va/F5, which is more ventral than the area 45 site shown in Fig. 8. See
manuscript text for details and Supplementary Table 7 for a summary of the significantly activated anatomical regions.
FOP
n = 75 stim trials
xyz = -21,31,17.5
Area 45
site
Electrode tract Area 45
site
Left lateral
Right medial
Left medial
Right lateral
Left VPFC (area 45) microstimulation (M4)
D
V
AP
D
V
AP
D
V
PA
D
V
PA
5 mm
2.3 15
0.05 10–48 Sagittal
Anterior
Dorsal
Axial
Right
Anterior
Coronal
Right
Dorsal
z score
P value
cluster corrected
VLPFC
Figure 8 | fMRI results from microstimulating frontal cortex area 45. Format as in Fig. 6. Top right panels show the electrode position and targeting
approach for this experiment. Bottom panels show the results from stimulating area 45. See manuscript text for details and Supplementary Table 6 for a
summary of the significantly activated anatomical regions. FOP, frontal operculum; VLPFC, ventrolateral prefrontal cortex.
Left lateral
Right medialLeft medial
Left operculum (insula) microstimulation (M3)
D
V
AP
D
V
AP
D
V
PA
FOP
aSTP
aSTS
5 mm
n = 75 stim trials
2.3 15
0.05 10–48
Operculum
site
Operculum
site
Electrode tract
xyz = –14,26,8
z score
P value
cluster corrected
D
V
PA
Right lateral
Figure 10 | fMRI results from microstimulating the frontal operculum. Format as in Fig. 8. Top right panels show the electrode position and targeting
approach for this experiment. Bottom panels show the results from stimulating the frontal operculum (FOP, compare with Figs 8 and 9). See manuscript
text for details and Supplementary Table 8 for a summary of the significantly activated anatomical regions.
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Discussion
The results, obtained using combined microstimulation and fMRI
to chart primate frontotemporal effective connectivity, challenge
the notion that all non-primary brain regions have a strong
functional impact on the frontal lobe. We observed that
stimulation of certain earlier auditory processing regions, such
as the lateral auditory belt, can significantly activate frontal
cortex, consistent with neuroanatomical tracer studies5,8,36.
However, stimulating further downstream auditory stages, such
as voice-sensitive cortex in anatomical areas Ts1/Ts2 is seen to
engage primarily an ipsilateral anterior temporal lobe network,
only parts of which activate frontal cortex when stimulated. This
study, therefore, supports notions of alternative arrangements of
parallel processing streams4,7,10,11, suggesting how these can
occur in the primate ventral auditory processing stream. We
discuss below how the results provide an important effective
connectivity perspective that is informed by neuronal
tractography and can potentially disambiguate neuroimaging
findings, which are often obtained from bidirectional connectivity
data29.
In relation to prior neuronal tractography studies, our results
reveal and demonstrate an interesting paradox in auditory
temporal to frontal connectivity. The observation from neuronal
tractography studies5and our effective connectivity results (Figs 6
and 7) clearly show that auditory belt areas target frontal cortex.
Thus, auditory cortical processing as early as the second stage has
a direct functional impact on, at least, ventro- and dorsolateral
frontal cortex, and our combined microstimulation and fMRI
results from the lateral belt confirm these general findings. The
unresolved question was whether all non-primary auditory
regions would affect frontal cortex potentially more strongly
than would early auditory areas8,25,27. Here we show that a
downstream fMRI-identified voice-sensitive cluster in the aSTP
(located within anatomical areas Ts1/Ts2, which represent the
fourth or fifth stage of auditory cortical processing) does not
prominently activate frontal cortex when stimulated. Notably,
only by stimulating an identified functional target of this region
in the adjacent multisensory aSTS did we observe prominent
frontal activation involving, in particular, orbital frontal cortex.
Given that both the aSTS and frontal cortex are considered to be
at a higher processing level than the auditory sites that we
stimulated, that is, aSTP or lateral belt), our results reveal that
certain processes, such as those in the auditory lateral belt, can
gain functional access to frontal cortex, while others, such as
those in the anterior voice-sensitive cortex, engage a more local
multisensory network before gaining access to orbital frontal
cortex.
Classically, the Ts1/Ts2 anatomical region was considered as
association (multisensory) cortex. However, at least parts of these
anatomical areas on the aSTP are now known to contain a voice-
sensitive region. This region appears to preferentially respond to
voice-identity content in communication sounds15–18,43,
although other voice-preferring clusters have also been
identified with fMRI in the human and monkey brain15,16,44.
Neurophysiological study of the anterior voice-sensitive region in
monkeys shows that its constituent neurons are sensitive to
different types of auditory inputs generally17,21 and differ in their
functional characteristics from neurons in the adjacent
association cortex of the aSTS. The aSTS, by comparison, is less
auditory feature sensitive and shows greater specificity in
multisensory influences18 (also see refs 19–21,45). Thereby,
these prior observations in the context of the current findings
would suggest that the orbital frontal targets of the aSTS receive
multisensory input from parts of an anterior temporal network,
and that the aSTP interacts with this network to indirectly gain
functional access to frontal cortex.
Neuronal tractography and computational studies in maca-
ques7,10,11 and recent analyses of neuroimaging connectivity data
in humans, macaques and other animals have noted exceptions to
a unique parallel processing organization4, stemming primarily
from work in the visual system. For example, the visual frontal
eye fields appear to be an exception in the visual processing
hierarchy in that they send strong feedforward laminar
projections to dorsal stream visual areas in the temporoparietal
cortex11. This is unusual as the frontal areas tend to provide
feedback projections to upstream visual processing areas. As
other examples, recent analyses of human and monkey
connectivity data suggest that local clusters of processing are
the rule rather than the exception, and that certain brain regions
act as hubs with longer-range projections that interconnect
different clusters. Our results suggest that association cortex in
the aSTS is likely to be an important temporal lobe site for the
access to frontal cortex. However, possibly because many of the
neuroimaging approaches are based on bidirectional connectivity
data, the results are not always consistent with known neuronal
tractography connectivity patterns. For example, in some
neuroimaging results human primary auditory cortex is seen to
have some of the longest range projections, longer than
association cortex46. Moreover, connectivity patterns in
diffusion-weighted imaging data from humans and monkeys
showing the clearest connectivity patterns appear to involve the
dorsal frontoparietal and frontotemporal pathways47.By
comparison, the ventral frontotemporal pathways are more
difficult to delineate, in part because of crossing fibers in the
uncinate fasciculus and extreme capsule.
The current study is an important complement to neuroima-
ging and neuroanatomical/neurophysiological work, providing
insights on effective connectivity. However, neuroimaging-based
approaches, ours included, do not have the specificity of neuronal
tractography studies that can evaluate laminar projections to
identify feedforward and feedback projections, and thus inform
us on neuroanatomical hierarchies. Nonetheless, as we see in our
study and others have noted for the visual system48, anatomically
defined hierarchies need not be correlated with neuroimaging or
neurophysiologically based topographies, the latter of which can
be used to delineate the level of functional processing complexity.
Our study was informed by work identifying the
neurophysiological and neuroanatomical processing stages of
the auditory lateral belt5,8,13,25,49,50 and information on voice-
sensitive cortex in the macaque Ts1/Ts2 regions14,16–18,22,51.
Also, our ‘control’ experiments stimulating the aSTS, two fields in
the lateral belt and three in the frontal cortex, are remarkable in
that, any limitations of DES and fMRI notwithstanding, they
seem to recapitulate the key findings from anterograde neuronal
tractography findings, as we have noted above. Thus, although an
anatomically based hierarchy would place the aSTP as an
anatomical stage in between the lateral belt and aSTS, our
results show instead that aSTP stimulation does not prominently
activate the frontal cortex (apart from the operculum in the
majority of cases), whereas microstimulating the lateral belt and
aSTS does result in significant activity of the orbital/ventral
frontal cortex.
It is important to consider to what extent the results can and
cannot account for alternative explanations, especially since the
approach of combined DES and fMRI is not yet well understood
(for reviews, see refs 40,52). Trivial explanations cannot easily
account for the differences in aSTP versus aSTS activation of the
OFC. For example, the observation of greater OFC activity by
aSTS but not by aSTP stimulation was supported by whole-brain
and hypothesis-driven ROI analyses (the ROI were conducted at
the individual and group levels), thus the main results seem to be
statistically robust. Also stimulation trial numbers were matched
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between aSTS and aSTP comparisons, the stimulation current was
fixed, and the animals were anesthetized (so that drifts in
attention or any task-dependent effects would not contribute,
both of which are known to be able to influence the magnitude of
fMRI effects from DES32). The effects of stimulating the frontal
eye fields, which reproduces some of the effects of attention, can
differ depending on the locations activated relative to bottom-up
influences from visual input33. Thus, given that stimulus and
task-dependent effects might affect the findings sufficiently, and
these effects also likely differ by site stimulated, studying effective
connectivity in anesthetized animals seemed warranted as a first
approach. It remains an interesting open possibility that
presenting communication sounds varying in voice-identity
content, with or without an active task, might have elicited
stronger activity in frontal cortex in combination with
microstimulation of the aSTP.
Any choice of anaesthesia could affect the BOLD response,
although it seems unlikely that the anaesthesia protocol
differently affected the aSTP and aSTS sites, both of which are
separated by a few millimetres of white matter. Also, the aSTS site
elicited robust activity in the OFC, so it is certainly the case that
stimulating specific temporal lobe sites (lateral belt included)
could robustly activate parts of the frontal cortex. Our anaesthesia
protocol using remifentanil has been developed to minimally
affect regions such as the ones reported here. Moreover, all of the
approaches that we used for fMRI localization or microstimula-
tion in anesthetized animals have been compared with the results
obtained from awake animals and shown to be largely compar-
able to a number of different visual and auditory pro-
cesses16,30,31,37–39 (for additional discussion of the impact of
the anaesthetic on the BOLD response see the Supplementary
Discussion).
Other alternative, not necessarily mutually exclusive, inter-
pretations either find little support or cannot be excluded by our
results. For example, is it the case that more robust activation of
the aSTP might engage OFC, comparably to what we see with the
aSTS? Our data do not appear to provide much support for this
possibility, since the most statistically robust aSTS versus aSTP
microstimulation result in activating OFC and MPFC that we
obtained coincides with the most robust activation of the aSTP
(Supplementary Fig. 6). However, on the question of whether
other regions might need to be co-activated along with the aSTS
to cause an effect in OFC, this remains an interesting possibility.
The main region that was consistently recruited with aSTS
stimulation but not aSTP stimulation was the OFC. However, a
number of anterior temporal lobe regions were more strongly
activated by aSTS than aSTP stimulation, many of which are
known to project to frontal cortex (Figs 3–5; Supplementary
Tables 1–3). Thus, although aSTP stimulation can significantly
activate these same anterior temporal lobe regions, it remains
possible that stronger activation of these regions by aSTS
stimulation contributed to the stronger OFC activity seen.
Neuronal tractography results show anterograde projections from
the aSTS to the OFC, thus the elicited OFC activity might not
depend on the co-activation of other regions. However, the
possibility that co-activation of certain regions is required cannot
be fully excluded without, for example, inactivating these said
regions and seeing whether microstimulation of the aSTS would
still activate the OFC.
Microstimulation and fMRI enabled us to chart the effective
connectivity of a number of brain regions, in a way that, to our
knowledge, has not been done before. For instance, we first
identified the functional targets of a site, some of which were then
stimulated to identify which new regions were significantly more
activated by stimulating the demonstrated targets of a particular
site. This approach aimed to harness what has otherwise been
noted as a limitation of DES, that is, what appears to be relatively
more restricted rather than extensive synaptic propagation40 (also
see refs 32–35). Namely, with DES there is evidence that gamma-
aminobutyric acid (GABA)-ergic intracortical inhibition in the
target region prevents the activity response from loosely
propagating to other cortical afferents30. However, direct
connections should not be assumed because corticosubcortical–
cortical activation and antidromic activation remain possible and
should be considered when interpreting the results. Nonetheless,
our use of ‘effective connectivity’ is in line with the original
definition, as a measure of the impact of one neural system on
another either directly or indirectly29. This is distinguished from
undirected or bidirectional functional connectivity.
Studies of combined microstimulation and fMRI, ours
included, cannot precisely localize the stimulating electrode to a
particular cortical layer. Also, current-spread measurements (in
our case at least 0.62 mm radius31) and prior work with DES
indicate that the most excitable (pyramidal) cells in the middle
layers of the cortex are stimulated53. Optogenetic techniques
enable greater selectively in optically simulating specific neuronal
subgroups, which are ones that express genetically transfected
channel rhodopsins. However, such an approach is also likely to
engage intracortical inhibition in the target site, which although
limiting loose transcortical propagation54, appeared to be an
advantage in this study. Also, at least currently, combined
optogenetic and fMRI studies in monkeys require cell-nonspecific
genetic promotors55 to elicit robust-enough neuronal responses
in primates that can be measured with fMRI. Thus, similar to
microstimulation, only the most excitable cells in the cortex
would be optogenetically stimulated. The limitations of the
approach notwithstanding, we included several control
stimulation experiments that recapitulated a number of key
established findings from the neuronal tractography literature.
This provides an important point of reference and helps to
interpret the results of microstimulating the aSTP. Other studies
using combined DES and fMRI of cortical regions in the
somatosensory35 or visual system32–34 have also reported that a
number of their results are consistent with the prominent
projection patterns reported in neuronal tractography studies. All
in all, our results suggest that the reported approach can be used
to good effect to target multiple brain sites with considerable
precision, and the results extend our understanding of effective
connectivity in the primate brain.
In conclusion, our observations provide evidence for different
forms of effective connectivity within the auditory ventral
processing stream. We obtained evidence that stimulation of an
anterior voice-sensitive region in the aSTP does not elicit
significant functional activity in the frontal cortex but appears
to engage primarily an anterior ipsilateral temporal lobe network.
These results are in stark contrast to those obtained by
stimulating upstream auditory areas in the lateral belt or a
presumed further downstream site in the multisensory aSTS, all
of which result in activation of frontal cortex. The findings
suggest that certain brain regions in the primate ventral temporal
pathway rely on adjacent processes before gaining access to the
frontal cortex, at least in the anesthetized preparation. The results
combine with other notable exceptions, primarily obtained in the
visual system, challenging a unique form of organization of the
different processing streams in the brain.
Methods
Study subjects.Four adult male rhesus monkeys (Macaca mulatta) were studied,
age ranged from 5 to 7 years. All procedures were approved by the local authorities
(Regierungspra
¨sidium Tu¨bingen, Germany; Referat 35, Veterina
¨rwesen) and were
in full compliance with the guidelines of the European Community (EUVD 86/609/
EEC) for the care and use of laboratory animals. The sample size was chosen to
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minimize the numbers of animals studied while ensuring that the key observations
are supported in at least two–three of the animals.
Anaesthesia protocol.An extensive description of the handling and anaesthesia
procedures was reported previously16,30,31,37–39 (also see Supplementary Text).
In brief, the handling and anaesthesia protocols ensure stress-free treatment
of the animals, while, at the same time, preserving neural responses to sensory
stimulation. The animals were premedicated with glycopyrrolate (intramuscular
0.01 mg kg 1) and keta mine (intramuscular 15 mg kg 1), and then a catheter was
inserted into the saphenous vein. Animals were then preoxygenated and prepared
for intubation with a combination of short-acting drugs (fentanyl at 3 mgkg1,
thiopental at 5 mg kg 1and the muscle relaxant succinyl-choline chloride at
3mgkg1). The trachea was then intubated and the lungs were ventilated at 25
strokes per min. We maintained anaesthesia with remifentanil (0.5–
2mgkg1min 1) in combination with a fast acting paralytic, mivacurium
chloride (5 mg kg 1h1). Because the fMRI BOLD signal is very sensitive to
changes in body temperature, oxygenation, pH and blood pressure, the
physiological state of the animal was monitored continuously and maintained
tightly within the normal limits. Body temperature was strictly maintained at
38–39 °C, and end-tidal CO
2
and oxygen saturation were kept constant at
33 mm Hg and over 95%, respectively. Acidosis was prevented by administering
lactated Ringer’s solution with 2.5% glucose, infused at 10 ml kg 1h1.
Intravascular volume was maintained by administering colloids (hydroxyethyl
starch, 20–30 ml over 1–2 min or 20 ml kg 1h1). We have measured
catecholamines and optimized dosages to ensure unaffected physiological
responses at normal catecholamine concentrations38. Functional data acquisition
started B2 h after the start of animal preparation, following acquisition of a high-
resolution anatomical scan. The Supplementary Text has a more extensive
consideration of the effects of the anaesthesia protocol on the BOLD response.
MRI and fMRI data acquisition.Measurements of the fMRI blood oxygen level
dependant (BOLD) signal were made on a non-human primate dedicated, vertical
4.7-Tesla MRI scanner (Bruker BioSpin, Ettlingen, Germany). Signals were
acquired using a birdcage radiofrequency coil. The animals were scanned while
seated in a customized primate scanning chair with their head held by a stereotactic
device. Functional MRI data were acquired using a gradient-recalled echo planar
imaging sequence with the following typical parameters: echo time, TE: 20 ms; TR:
1.5 s; flip angle: 60°; 22 slices, 2-mm thickness; in-plane field of view: 9.6 9.6 cm2,
on a grid of 128128 voxels, with a voxel resolution of 0.75 0.75 2mm
3.
Anatomical images for localizing the electrode were obtained in axial, coronal or
sagittal planes using T2-weighted FLASH (fast low-angle shot) sequences
(Supplementary Fig. S1) with typical parameters TE: 10 ms; TR: 1,000ms; flip
angle: 60°; 22–35 slices; in-plane field of view: 9.6 9.6 cm2, on a grid of 256 256
voxels. Anatomical scans in register with each functional scanning experiment were
also obtained using a three-dimensional T1-weighted MDEFT (modified driven
equilibrium Fourier transform) sequence with typical parameters TE: 5 ms; TR:
20 ms; flip angle: 20°; 128 slices; in-plane field of view: 12.8 12.8 cm2, on a grid of
256 256 voxels, with typical voxel re solution of 0.5 0.5 0.5 mm3; four
segments.
Functional MRI localizers.Before the microstimulation experiments, the four
animals (M1–M4) underwent fMRI localizer experiments, as follows. The func-
tional localization experiments included tonotopic auditory cortex mapping using
tones and band-passed noise at different center frequencies37,56. Analyses
identifying the reversals of tonotopic sound-frequency preference gradients and the
approximate location of the core auditory cortex were used to delineate auditory
cortical fields (ACF; Supplementary Fig. S5). Briefly, sounds at different frequencies
elicit frequency selective fMRI activity patterns throughout the auditory core and
belt. Gradient analyses of the tonotopic gradient reversals reveal the approximate
location of borders between core and belt fields in the anteroposterior direction. A
primary auditory cortex localizer based either on comparing tone versus band-
passed noise responses (the latter of which are stronger in the auditory belt) and/or
using thresholded tone responses (which are stronger in the core) helps to
distinguish auditory core versus belt fields. Auditory parabelt or downstream fields
are not thought to be tonotopically organized and are delineated in relation to the
position between the tonotopically organized core and belt fields and the remaining
anatomical regions thought to reside on the STP. For additional details please see
refs 16,37,56.
We also mapped anterior voice-sensitive clusters using voice versus non-voice
and, time permitting, voice-identity adaptation localizers16. In brief, the fMRI
activity response to a stimulus category of macaque vocalizations produced by
many individuals (that is, many voices) is compared with a stimulus category of
non-voice sounds (that is, natural and environmental sounds; see Supplementary
Figs 1–4). Since our hypotheses were specifically for voice-sensitive clusters in the
Ts1/Ts2 regions anterior to the tonotopically organized core and belt fields (Fig. 1),
we restricted our analysis of voice-sensitive clusters to the Ts1/Ts2 region
(Supplementary Figs 1–4). Thus, the strongest voice-sensitive clusters in these
regions were targeted for microstimulation. For additional details on the fMRI
voice localization procedure please see refs 16,17. Finally, in one experiment with
macaque 3 we were also able to identify an anterior face-sensitive cluster in the
fundus of the STS using a face versus non-face fMRI localizer38,57 (Supplementary
Fig. 10).
Microstimulation approach.Chambers to target fMRI-identified clusters or other
stereotactically determined anatomical sites were implanted using neurosurgical
targeting approaches17. We targeted for microstimulation the anterior voice-
sensitive clusters in the aSTP, within anatomical areas Ts1/Ts2 (Fig. 2,
Supplementary Figs 1–4). We also targeted an upper-bank aSTS anatomical region,
which we observed was activated by aSTP stimulation (localized to anatomical field
TPO; Figs 3–5; Supplementary Figs 1–4). The aSTS site was located 4–6 mm below
the aSTP site and separated from it by white matter. As reported, for some
experiments we also targeted sites within other anatomical areas, using structural
MRI scans and stereotactic coordinates24.
Electrodes were custom-made platinum/iridium glass-coated electrodes (see
below). MRI was used to identify the electrode position by the local signal loss
caused by the platinum/iridium microfilament in the electrode (Fig. 2;
Supplementary Figs 1–4). Because the tip of the electrode cannot be localized
precisely, we stopped the approach to the target site 4–5 mm short of it and then
slowly advanced the electrode while continually monitoring neuronal responses.
This allowed us to evaluate the silent transition areas that the electrode passed
through, such as those in the lateral sulcus and in the white matter between the
aSTP and aSTS sites. Once neuronal activity increased again as the electrode
entered the cortical grey matter, we advanced the electrode B1 mm further so as to
be well within the grey matter. An additional set of MRI scans was then acquired to
identify the approximate electrode placement, although we could not identify its
laminar location (Fig. 2; Supplementary Figs 1–4).
Microstimulation procedure.The microstimulation procedure has been reported
elsewhere in detail30,31,53 as have the methods we used for conducting
simultaneous electrophysiological recordings and MRI58. In brief, induction
voltages caused by gradient coil switching were compensated for by measuring the
induced currents on the animal with rotationally symmetric sensors placed around
the electrode. Current was passed back to the animal via a wire in the mouth to
cancel the currents measured by the sensor (see ref. 58, for details). In addition, for
this study we used a custom-built constant current source, with the aim of
compensating for the capacitance of the cable that delivered the stimulation. The
compensation circuit allowed calculating the instantaneous amount of current
needed to charge the cable capacitance by measuring the differential of the voltage
across the cable. The current needed to achieve this was then added to the desired
current30,31,53.
We used glass-coated platinum-iridium electrodes, with impedances of
75–250 kO. Impedances were checked throughout the experiments and micro-
stimulation was not conducted with electrodes that had impedances o75 kO.All
reported experiments used a constant current of 500 mA. An experiment was
terminated if a voltage threshold of 10 V was breached, which usually indicates that
the electrode impedance had dropped below 75kOand could compromise the
quality of the results31. The current amplitude, pulse duration, train duration and
stimulation frequency were controlled digitally by using the QNX real-time
operating system (Fig. 2). We used a charge-balanced, biphasic-pulse procedure
(consisting of square-wave pulse durations of 0.2 ms positive or negative)30,31. The
stimulation frequency was 200 Hz, and included numerous non-stimulation
periods to allow for neuronal refractory periods (Fig. 2). The stimulation protocol
was presented in blocks, such that 10 (1.5 s) fMRI volumes were obtained during a
stimulation ‘trial’, resulting in a trial length of 15 s. Each trial consisted of 4.5 s of
no stimulation, 3 s of stimulation and 7.5s of no stimulation (Fig. 2). The numbers
of microstimulation trials obtained with fMRI are reported in the figures. Also, all
analytical comparisons between the aSTP and aSTS experiments were matched in a
numbers of trials.
Functional MRI analyses.For each stimulation experiment, we performed a fixed-
effects General Linear Analysis (FEAT, FSL59) contrasting fMRI BOLD responses
to stimulation versus no-stimulation periods. The analysis of stimulation versus
no-stimulation was evaluated using a hemodynamic response model and evaluated
at the cluster corrected (Po0.05) level (2 mm smoothing full-width half
maximum). The contrast between the effects of stimulating aSTS and aSTP (Fig. 2)
is shown at the Po0.001 uncorrected level simply for consistency across all
animals: we confirmed that the observation of aSTS versus aSTP stimulation
resulting in greater orbitofrontal activity was also significant at the Po0.05 cluster-
corrected level in the majority of animals and experiments (for M1 in Fig. 3 and
M3 in Fig. 5 and for the data shown in Supplementary Fig. 6; also see
Supplementary Tables 1–3 and 9–12 for voxels summary statistics).
With the animal’s own anatomical scans serving as intermediates, the results of
these analyses were registered to a standard macaque template brain60, which is
registered to a macaque atlas in stereotactic coordinates24 as well as a digital atlas
developed from it61. This allowed us to determine the anatomical areas within
which the significant activity clusters occurred. The results were also registered to a
FreeSurfer (http://surfer.nmr.mgh.harvard.edu/) surface-based representation of
the standard template monkey brain60. Anatomically defined ROIs in the anterior
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auditory cortex (rostral core/belt fields) or OFC were defined in reference to the
macaque brain atlas24,61. For statistically testing the voxel-based responses in the
ROIs, the ROIs were registered back to the animals’ own functional imaging data.
This helped avoid overinflating the number of voxels used for analysis (which
would happen if instead we had registered the functional scans to the higher
resolution anatomical space and used this for the ROI analyses). These ROI data
were also analysed with the animals’ data combined using a mixed-effects ANOVA
with a random between-subjects factor of ‘monkey’ and a fixed within-subjects
factor of ’stimulation site’. Hemisphere was also added to these models as needed
(see Results for further details).
Histological processing.At the end of all the experiments, each of the four
animals was deeply anesthetized and trans-cardially perfused with saline followed
by 4% paraformaldehyde in 0.1 M phosphate buffer (PB; pH 7.4).The for-
maldehyde-fixed brain was extracted, photographed and blocked in the coronal
plane. The brain was stored in 10% glycerol with 2% dimethyl sulfoxide in 0.1 M
PB and then transferred to 20% glycerol with 2% dimethyl sulfoxide in 0.1 M PB
for up to 6 days. Frozen sections were cut in coronal planes at 40-mm thickness and
adjacent sections were stained for Nissl (M1-4), SMI-32 or parvalbumin (M1). This
allowed us to compare with the brain atlas histological slices24 and our MRI
sections for further confirmation of some of the anatomical site positions
(Supplementary Fig. 1).
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Acknowledgements
We thank M. Augath for MRI experimental support and R. Saunders and D. Yu for
invaluable assistance with histological processing. T. Griffiths, M. Kaiser, L. Orton, C.
Perrodin, A. Rees, L. Romanski, K. Saleem, B. Scott and B. Wilson provided helpful
comments on or discussion of the manuscript. Support provided by Max Planck Society
(N.K.L.); Alexander von Humboldt Foundation (C.I.P.); Wellcome Trust Investigator
Award WT102961MA (C.I.P.); NIH-R01DC003489 (J.P.R.), NIH-R56NS052494 (J.P.R.);
NSF PIRE OISE-0730255 (J.P.R.); NIMH, NIH (M.M.).
Author contributions
C.I.P., Y.K., M.M., J.P.R. and N.K.L. designed research; C.I.P. and Y.K. performed
research; C.I.P., Y.K., M.M., J.P.R. and N.K.L. contributed materials/analytic tools; C.I.P.,
Y.K. and A.M. analysed data; C.I.P. wrote the paper with input from J.P.R., M.M., A.M.,
Y.K. and N.K.L.
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How to cite this article: Petkov, C. I. et al. Different forms of effective connectivity
in primate fronto-temporal pathways. Nat. Commun. 6:6000 doi: 10.1038/ncomms7000
(2015).
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