Long-Range Neuronal Circuits
Underlying the Interaction
between Sensory and Motor Cortex
Tianyi Mao,1,2Deniz Kusefoglu,1,2Bryan M. Hooks,1Daniel Huber,1Leopoldo Petreanu,1and Karel Svoboda1,*
1Janelia Farm Research Campus, HHMI, 19700 Helix Drive, Ashburn, VA 20147, USA
2Present address: Vollum Institute, Oregon Health & Science University, Portland, OR 97239, USA
In the rodent vibrissal system, active sensation and
sensorimotor integration are mediated in part by
connections between barrel cortex and vibrissal
motor cortex. Little is known about how these struc-
tures interact at the level of neurons. We used Chan-
nelrhodopsin-2 (ChR2) expression, combined with
mouse motor cortex. Barrel cortex axons preferen-
tially targeted upper layer (L2/3, L5A) neurons in
motor cortex; input to neurons projecting back to
barrel cortex was particularly strong. Barrel cortex
input to deeper layers (L5B, L6) of motor cortex,
including neurons projecting to the brainstem, was
weak, despite pronounced geometric overlap of
dendrites with axons from barrel cortex. Neurons in
different layers received barrel cortex input within
stereotyped dendritic domains. The cortico-cortical
neurons in superficial layers of motor cortex thus
couple motor and sensory signals and mightmediate
sensorimotor integration and motor learning.
Rodents move their large whiskers, also called facial vibrissae,
through space to locate and identify objects (Carvell and
Simons, 1990; Hutson and Masterton, 1986; Knutsen et al.,
2006; Krupa et al., 2001; O’Connor et al., 2010a). Conversely,
whisker movements are guided by sensory feedback (Mitchin-
son et al., 2007; Nguyen and Kleinfeld, 2005). These interactions
between sensory and motor systems are crucial for haptic
perception (Diamond et al., 2008; Gibson, 1962; Wolpert et al.,
1995). Sensorimotor integration in whisker-based somatosensa-
tion is mediated by brain structures that form a series of nested
loops, at the levels of the brainstem, thalamus, and cerebral
cortex (Diamond et al., 2008; Kleinfeld et al., 1999). Little is
known about the cellular architecture of these different loops.
A prominent loop occurs at the level of the cerebral cortex (Ar-
onoff et al., 2010; Chakrabarti and Alloway, 2006; Donoghue and
Porter, 1995; Miyashita et al., 1994; Porter and White, 1983; Vei-
nante and Desche ˆnes, 2003; Vogt and Pandya, 1978; Welker
et al., 1988; White and DeAmicis, 1977). Vibrissal primary
sensory cortex (vS1, barrel cortex) and vibrissal primary motor
cortex (vM1) are reciprocally connected. One barrel column in
vS1 projects to a band of vM1, with its long axis in the anterior/
posterior (A/P) direction (Aronoff et al., 2010). vM1 projects
diffusely to vS1, covering most of the barrel field and adjacent
areas (Veinante and Desche ˆnes, 2003).
Reciprocal cortical connections have also been detected in
neurophysiological recordings in vivo. Following the deflection
of a whisker, excitation first ascends into vS1 and then rapidly
propagates to vM1 (Farkas et al., 1999; Ferezou et al., 2007;
Kleinfeld et al., 2002). Neuronal activity in vS1 is modulated by
whisking (Curtis and Kleinfeld, 2009; de Kock and Sakmann,
2009; Fee et al., 1997; O’Connor et al., 2010b), mediated in
part by an efference copy-like signal originating in vM1 (Ahrens
and Kleinfeld, 2004; O’Connor et al., 2002). Integrating signals
related to whisking and whisker deflection might underlie object
localization (Curtis and Kleinfeld, 2009; Diamond et al., 2008).
The detailed neural circuits underlying the vS1 ) / vM1 loop
are poorly understood. A circuit diagram, based on functional
connections between defined cell types, might reveal the
primary loci where sensorimotor associations are formed. In
addition to the connectivity between cell types, the interactions
between neurons in vS1 and vM1 depend on the locations of
synapseswithin thedendritic arbors ofthe postsynaptic neurons
(Larkum et al., 2004; London and Ha ¨usser, 2005). Anatomical
methods, relying on visualizing axons and dendrites with light
microscopy, have often been used to predict circuits (Binzegger
axodendritic overlap is not necessarily a good predictor of
functional connection strength (Callaway, 2002; Dantzker and
Callaway, 2000; Petreanu et al., 2009; Shepherd et al., 2005;
White, 2002). Alternatively, electrophysiological methods that
detect functional synapses, including paired recordings and
glutamate uncaging-based methods, have been applied to
map local circuits within vS1 (Bureau et al., 2006; Hooks et al.,
2011; Lefort et al., 2009; Lu ¨bke and Feldmeyer, 2007; Schubert
et al., 2003, 2006; Shepherd et al., 2003, 2005; Shepherd and
Svoboda, 2005) and vM1 (Hooks et al., 2011). These techniques
require the preservation of pre- and postsynaptic neurons and
their axonal processes within a brain slice and are thus mostly
limited to local circuits (Luo et al., 2008).
Neuron 71, 111–123, October 6, 2011 ª2011 Elsevier Inc. 111
Although a subset of long-range connections between vS1
and vM1 can be preserved in brain slices (Rocco and Brumberg,
2007), it is unclear how complete the preserved circuit is. We
previously applied subcellular Channelrhodopsin-2-assisted
circuit mapping (sCRACM) to chart the connections made by
long-range projections onto vS1 neurons (Petreanu et al.,
2009). sCRACM measures connections between presynaptic
neurons, defined by ChR2 expression, and postsynaptic
neurons, defined by whole-cell recordings. sCRACM relies on
photostimulating axons, which can be efficiently excited even
when severed from their parent somata. Therefore, sCRACM
can map connections between defined neuronal populations
over long length scales, not limited to circuits preserved in brain
slices. sCRACM also provides an estimate of the spatial dis-
tribution of synapses made by ChR2-positive axons onto the
dendritic arbors of recorded neurons.
Here, we applied anatomical methods and sCRACM to map
inputs from vS1 onto neurons in vM1. vM1 neurons in upper
layers (L2/3 and L5A), which harbor mostly cortico-cortical
neurons, receive strong input from vS1. These neurons also
provide the majority of the projection back to vS1. In contrast,
deep layer neurons (L5B and L6), which include the ‘‘cortico-
fugal’’ neurons that project to motor centers in the brainstem
and elsewhere, received only weak input from vS1.
Reciprocal Connections between vS1 and vM1
We characterized the projections between vibrissal somatosen-
sory cortex (vS1) and vibrissal motor cortex (vM1) using viral-
S1 available online). vS1 was identified by the presence of large
barrels. vS1 layers were defined according to well-established
cytoarchitectural criteria (Bureau et al., 2006; Groh et al., 2010).
Individual layers contain distinct sets of neurons, with different
projection patterns and inputs (Groh et al., 2010; Hattox and
Nelson, 2007; Sato and Svoboda, 2010; Svoboda et al., 2010).
We labeled vS1 neurons by infection with recombinant adeno-
associated viruses (AAV) (Chamberlin et al., 1998) expressing
eGFP or tdTomato, and imaged the projections of the infected
neurons throughout the brain using a high-resolution slide
scanner (excluding most of brainstem and spinal cord). Infected
neurons were distributed over several barrel columns (diameter
of infection site <1.5 mm) (Figures 1A and 1B), mainly in L2/3
and L5 (Figure S1A). Axonal projections were seen in multiple
cortical and subcortical targets. We quantified these projections
by integrating the fluorescence intensity over the sections con-
Experimental Procedures). The projections from anatomically
strongest to weakest (annotations refer to Paxinos and Franklin
)wereasfollows:striatum (Str),secondary somatosensory
cortex (S2), vM1 (including frontal association cortex [FrA]),
thalamic nuclei (Th) (including, posterior thalamic nucleus [PO],
reticular thalamic nucleus [RT], and ventral posteromedial
thalamic nucleus [VPM)]), superior colliculus (SC), ectorhinal/
perirhinal cortex (Ect), contralateral vS1, zona inserta (ZI),
primary sensory cortical region medial to vS1 (MS1), anterior
pretectal nucleus (APT), contralateral Ect, contralateral MS1, re-
uniens thalamic nucleus (Re)/rhomboid thalamic nucleus (Rh),
orbital cortex (OC), lateral parietal association cortex (LPtA), in-
fralimbic cortex (IL)/dorsal peduncular cortex (DP) (Figures
1B2, 1B3, 1C and S1B–S1H; see Experimental Procedures and
Supplemental Experimental Procedures). These data are quali-
1991; Hoffer et al., 2003, 2005; Hoogland et al., 1987; Welker
et al., 1988; White and DeAmicis, 1977) but also include projec-
tions that have not been reported (e.g., Re/Rh, OC and IL/DP),
andpoorlycharacterized medialparietal corticalareas, including
MS1 and LPtA.
One of the most prominent projections was vS1 / vM1. Stim-
ulating the vS1-projection zone in vM1 in vivo, using microelec-
trodes (Donoghue and Parham, 1983; Ferezou et al., 2007; Li
and Waters, 1991; Matyas et al., 2010; Porter and White, 1983)
or ChR2 photostimulation (Hooks et al., 2011; Matyas et al.,
2010), causes whisker protractions at low stimulus intensities
(Figure S2). Simultaneous tracing with two viruses expressing
different fluorescence proteins (GFP or tdTomato) revealed that
the vS1 projection to vM1 and S2 were topographic (Figures 1D,
1E, and S3). The projection zone in vM1 shifted primarily in the
anterior-lateral direction as the site of labeling in vS1 moved
along a whisker row across arcs (Figure 1E3), in agreement with
previous studies in mouse (Welker et al., 1988) and rat (Hoffer
et al., 2005). The distance separating the injection sites was 1.5
The vS1 projection split into multiple distinct domains in vM1,
Apart from the boundary between layer 1 (L1) and layer 2 (L2),
vM1 cytoarchitecture is relatively indistinct (Figures 2A and S4),
and approaches for defining layers in the motor cortex vary
across studies (Brecht et al., 2004; Hooks et al., 2011; Weiler
et al., 2008). Here, we defined vM1 layers using a combination
of cytoarchitectural criteria and retrograde labeling of neurons
by injecting fluorescent microbeads into the vM1 projection
zones (Figures 2 and S4). L1 has few neurons. L5A and L2/3
contain high densities of vS1-projecting neurons (Figures 2B
and 2C). L5A corresponds to a light zone in bright field images,
continuous with L5A of sensory cortex (Weiler et al., 2008).
Compared to vS1, L5A in vM1 is relatively superficial (Figure S4).
As an agranular cortex, vM1 lacks a clearly defined layer 4 (L4).
However, we note that a distinct band between L5A and L2/3
contains neurons that were not labeled by any of the retrograde
labeling experiments (Figure 2C, dashed line separating L2/3
and L5A; Anderson et al., 2010). This layer, therefore, appears
to harbor mainly local neurons, similar to L4 in sensory cortex.
This band also overlaps with L4 markers, such as RAR-related
orphan receptor beta (mouse.brain-map.org) (Hooks et al.,
2011). However, in terms of its inputs, this band is not obviously
different from L2/3 and L5A and was therefore subsumed into
these layers for the analysis below. L5A separates L2/3 and
deeper layers (5B and 6). Layer 5B (L5B) is defined by the pres-
ence of pyramidal tract (PT) type neurons projecting to subcor-
tical targets, including the brainstem and other areas (Figure 2C).
In bright field images, layer 6 (L6) appears darker than L5B (Fig-
ure 2A). The L5B/L6 boundary corresponds to the lower extent
of brainstem-projecting PT type neurons (Figure 2C). L6 has a
high density of neurons projecting to the thalamus (Figure 2C).
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112 Neuron 71, 111–123, October 6, 2011 ª2011 Elsevier Inc.
StrS1+S2 FrAThcvM1 cStr RSA
StrS2vM1ThSCEctcvS1 ZIAPT cEctMS1*cMS1 OCRe/RhDP*LPtA
Figure 1. Mapping Output from Somatosensory Cortex (Barrel Cortex, vS1) and Vibrissal Motor Cortex (vM1)
(A–C) Viral injections in vS1 and projections to vM1 and other targets. (A) Schematic, injection in vS1 and projection to vM1. (B) Representative images of
injections in vS1 and projections to vM1 and other targets. (B1) AAV-tdTomato injected into vS1 (asterisks) and projection to vM1 (arrowhead). Dashed lines
Also shown are projections to second somatosensory cortex (S2), thalamus (Th), and ectorhinal/perirhinal cortex (Ect), and fibers passing through the internal
capsule (ic). (B3) Coronal section through vM1. (B4) Confocal image of vS1 axons in vM1, overlaid with a bright field image of the brain slice. (C) Fraction of vS1
output to various brain areas, rank-ordered by strength (quantified based on fluorescence; three separate experiments).
(D and E) Topographic projections from vS1 to vM1 and S2. (D) Schematic, pairs of injections in vS1and projections to vM1. (E1) AAV-eGFP and AAV-tdTomato
injected in nearby parts of vS1 (green, centered on barrel C2; red, centered on barrel C5) (additional examples in Figure S3). The fluorescence image is from
a section of flattened cortex, overlaid on a brightfield image showing the cytochrome oxydase stained section to highlight barrels (see Experimental Procedures).
(E4) Contrast-enhanced image showing projections to S2.
(F–H) Projections from vM1 to vS1 and other targets. (F) Schematic, injection in vM1 and projection to vS1. (G1) AAV-eGFP injected into vM1 (asterisks) and
projection to vS1 (arrowhead). Dashed lines correspond to the sections containing the injection site in vM1 (inj) and the projection site in vS1 (proj). (G2) Coronal
section through the injection site (asterisk) and projection to contralateral vM1. (G3) Coronal section showing vS1, S2, and dorsal lateral striatum (Str). (G4)
Confocal image showing vM1 axons in vS1. (H) Fraction of vM1 output to various brain areas, rank-ordered by strength (quantified based on fluorescence; two
SC, superior colliculus; Ect, ectorhinal/perirhinal cortex; cvS1, contralateral vS1; ZI, zona incerta; MS1, medial primary sensory cortex, medial to vS1 (also see
FigureS1);APT,anterior pretectalnucleus; cEct, contralateral side of ectorhinal/perirhinal cortex;cMS1,contralateral sideof medial primarysensorycortex; LPtA,
lateral parietal association cortex (see Figure S1); OC, orbital cortex; Re/Rh, both ipsilateral and contralateral sides of reuniens thalamic nucleus and rhomboid
associate cortex, also might include some intra-vM1 axons; cvM1, contralateral side of primary motor, and contralateral side of FrA; cStr, contralateral side of
striatum; RSA, retrosplenial agranular cortex; cOC, contralateral orbital cortex; cCl, contralateral side of claustrum; *one animal’s data not shown, either because
region of interest is on the same side as the viral infection. See also Figures S1–S4, Table S1, and Movie S1.
Neuronal Circuits between Sensory and Motor Cortex
Neuron 71, 111–123, October 6, 2011 ª2011 Elsevier Inc. 113
The deeper layers (L5B and L6) occupy more than half of the
depth of vM1. As additional data on local circuits becomes avail-
able, these layers may have to be subdivided further (Anderson
et al., 2010; Hooks et al., 2011).
In vM1, a band of vS1 axons ascended from the white matter
through most layers (Figure 1B3). Although vS1 axons arborized
in L1, they were excluded from the top-most ?20 mm (Fig-
ure 1B4), indicating that L1 in vM1 contains sublaminae that
participate in distinct circuits. Retrograde labeling experiments
revealed that these axons arise mainly from L2/3 and L5A in
vS1 (Figures S5A–S5B; Sato and Svoboda, 2010).
We next mapped the output from vM1 (Figures 1F–1H). A
cluster (diameter <1.5 mm) of neurons was infected throughout
the cortical layers in vM1 (Figure S1A). The projections (from
anatomically strongest to weakest) were as follows (Figure 1H):
Str, somatosensory cortex (including vS1 and S2), FrA (including
projections within vM1), Th (including PO, ventral-antero/
ventral-lateral thalamic nucleus [VA/VL], and VPM), contralateral
vM1, contralateral Str, retrosplenial agranular cortex (RSA), OC,
contralateral OC, SC, ZI, Re/Rh, contralateral Ect (cEct), contra-
lateral claustrum (cCl), and Ect (Figures 1G1–1G3, 1H, and
S1I–S1K; Experimental Procedures and Supplemental Experi-
mental Procedures; Miyashita et al., 1994; Porter and White,
1983). A prominent projection was vM1 / vS1. In vS1, vM1
axons ascended from the white matter and arborized in L5
and, most abundantly, in L1 (Figures 1G3 and 1G4; Cauller
et al., 1998; Petreanu et al., 2009; Veinante and Desche ˆnes,
connected in a reciprocal manner in mice.
ChR2-Based Mapping of Long-Range Neuronal
measure the strength of input from vS1 to excitatory neurons
injected in vS1
Distance to pia (normalized)
Figure 2. Relationship between Laminar Location
and Projection Targets in vM1
(A) Bright field image of a vM1 brain slice. The vertical lines
demarcate the recording locations. Horizontal lines indi-
cate layer boundaries.
(B) A representative retrograde labeling experiment.
Fluorescent microbeads were injected in vS1 and imaged
(C) Fluorescent microbeads were injected in brain areas
that are targets of vM1 projections. vS1, black; zona
inserta, ZI, magenta; superior colliculus, SC, gray; brain-
stem, BS, green; posterior thalamic nucleus, PO, blue;
three separate experiments for each target brain region;
15 experiments total. Bead-positive cells were mapped
and their density plotted against the relative cortical depth
(see Experimental Procedures). Error bars, SEM.
See also Figures S4 and S5 and Table S1.
across layers in vM1. AAV virus was used to
express ChR2 tagged with fluorescent proteins
(Nagel et al., 2003) (Venus [Petreanu et al., 2009]
or tdTomato) in vS1. In brain slices we recorded
from vM1 pyramidal neurons with dendrites
overlapping vS1 axons (Figures 3A and S4A).
In most experiments (except in Figures 6B, S6F, S8B, and
S8C) the bath contained TTX (1 mM), to eliminate action poten-
tials, and 4-AP (100 mM),to block the K+channels that are critical
for repolarizing the axon (Petreanu et al., 2009). Under these
conditions short laser pulses (1–2 ms) depolarized ChR2-
expressing axons in the vicinity of the laser beam and triggered
the local release of glutamate. CPP (5 mM) was added to the
bath to block nonlinear NMDA conductances in the postsyn-
aptic dendrites. Measurements of postsynaptic currents (EP-
SCsCRACM) then revealed the presence of functional synapses
between ChR2-expressing axons and the recorded neuron in
the vicinity (<60 mm) of the photostimulus (Petreanu et al.,
2009). Block of action potentials also prevented possible contri-
butions from polysynaptic pathways.
Stimuli were delivered on a grid pattern which covered the
entire dendritic arbor of the recorded cell (Figures 3A and 3B).
Maps were reproducible across iterations (repeated 2–4 times;
Figure 3C). Averaged EPSCsCRACMwere used as pixel values
in sCRACM input maps (Figure 3D). Aligning the dendritic arbor
of the recorded cell with sCRACM maps revealed the dendritic
locations where the synapses from ChR2-positive axons oc-
curred. Because of electrotonic filtering more distant inputs are
relatively more attenuated, and sCRACM maps represent
a soma-centric view of the spatial distribution of synaptic input
within the recorded neurons (Petreanu et al., 2009). Multiple
neurons were recorded sequentially in the same brain slice
(lateral distances <300 mm, with overlapping dendrites), under
identical conditions (Figure 3D). Within-slice comparisons of
input strength are necessary because ChR2 expression varies
The Strength of vS1 Input as a Function of Cortical Layer
We compared the strength of vS1 input to pyramidal neurons in
different layers in vM1 (Figure 4). We summed pixels with
Neuronal Circuits between Sensory and Motor Cortex
114 Neuron 71, 111–123, October 6, 2011 ª2011 Elsevier Inc.
significant responses (>63 standard deviation) to estimate input
strength (Figures 4C–4F; other analyses without thresholding
produced similar results; Figures S6D–S6I; also see Experi-
For all cells we compared the input strength to that of L5A
neurons, which received the strongest input from vS1. L2/3
neurons received similarly strong input (Figure 4C; p > 0.5,
signed-rank test). In experiments where input was detected in
one L5A cell (failures did occur in a small fraction of experiments
due to insufficient ChR2 expression), other L2/3 and L5A cells
also showed input. This suggests that most, perhaps all, L2/3
and L5A cells in the vS1 projection zone within vM1 receive input
In contrast to the upper layer neurons, many (but not all) L5B
and L6 cells did not receive detectable vS1 input. Input to large
pyramidal neurons in L5B was 7-fold weaker than input to L5A
cells on average (p < 0.001, signed-rank test); input to L6 was
10-fold weaker than input to L5A (p < 0.001, signed-rank test).
Together, these data show that the laminar location of the
soma is a key determinant of the strength of input from vS1.
L5A and L2/3 neurons, containing mostly cortico-cortical and
local cortical neurons, receive strong input from vS1. L5B and
L6, containing the vast majority of vM1 neurons projecting out
of the cortex, receive relatively little direct input from vS1.
The Distribution of vS1 Input within the Dendrites
of vM1 Neurons
We next analyzed the spatial distribution of vS1 input within the
dendritic arbors of vM1 neurons. sCRACM input maps were
averaged, aligned either on the pia (Figure 5A) or the soma (Fig-
ure 5B). Since the density of ChR2-positive axons varies
between preparations, the measured vS1 input varied greatly
across experiments. Therefore, individual sCRACM maps were
normalized before averaging, by dividing with the largest pixel
in a map. The average maps thus represent the relative distribu-
within a single, contiguous domain, centered on the soma,
approximately 50 mm above the peak of basal dendrite length
basal and apical domains. The basal domain was centered on
the basal dendrites, whereas the apical domain was on the
border between L1 and L2. When it was present, the input to
L5B neurons was primarily in the basal dendrites. Input to L6
neurons was mainly on the proximal apical dendrites. These
spatial distributions of input were also apparent in individual
maps (Figure S6A). In general, regions with large input corre-
sponded to high densities of dendritic length (Figure 5B). But
there were exceptions to this rule; for example, input to L6
targeted proximal apical dendrites, avoiding the denser basal
dendrites (Figure 5B4). These findings indicate that input from
vS1 targets specific domains within the dendritic arbors of vM1
The Strength of vS1 Input to PT Type Neurons
PT type neurons project to the brainstem reticular formation, the
facial nucleus and the spinal trigeminal nucleus (Grinevich
et al., 2005; Hattox et al., 2002; Miyashita et al., 1994). These
neurons are located in L5B, intermingled with pyramidal neurons
projecting to other targets (Nudo and Masterton, 1990) (Figures
2C, S5C, and S5D). Although L5B neurons received weak vS1
input on average (Figure 4D), a small fraction of cells received
strong input from vS1 (Figures 6A and S6). These outliers
were not necessarily near the L5A/L5B border (Figure S6B).
We thus wondered if L5B cells with large vS1 input might corre-
spond to PT type neurons projecting to brainstem. To test this
possibility, we injected ChR2 into vS1 and fluorescent micro-
beads into the reticular formation and facial nucleus. In vM1
slices werecorded frombead-labeled cellsinL5B andunlabeled
neurons in L2/3 and L5A in the same column. Responses in
bead-labeled neurons were small compared to upper layer
neurons (p < 0.001, signed-rank test), and indistinguishable
and the reconstructed dendrites of two sequentially recorded cells (L5A,
(B) Excitatory postsynaptic currents (EPSCsCRACM) recorded from the L5A cell
(magenta in A), evoked by photostimulation on a grid (black traces are re-
produced at higher magnification in C). EPSCsCRACMare caused by local
depolarization of ChR2-positive axons, triggered by blue light.
(C) EPSCsCRACM were reproducible across repetitions (three repetitions;
photostimulus locations as for black traces in B). Blue ticks indicate the
photostimuli.Theblueandgrayticks demarcate thewindowforcalculating the
response plotted in sCRACM input maps.
(D) sCRACM input maps. Left panel, L5A cell in (A). Right panel, L5B cell in (A).
The pixel value is proportional to the strength of input from ChR2-positive
axons to particular locations of the dendritic arbor. The triangles indicate the
soma locations. Two maps were obtained under the same stimulation and
See also Figures S4 and S5.
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Neuron 71, 111–123, October 6, 2011 ª2011 Elsevier Inc. 115
from unlabeled L5B neurons (p > 0.1, ranksum rest) (Figures 6C,
6D, S6E, and S6H).
Large pyramidal neurons have electrotonically complex struc-
ture (Johnston et al., 1996; London and Ha ¨usser, 2005). Distal
inputs are filtered and may rely on non-linear mechanisms for
amplification. We considered the possibility that detecting vS1
input at the soma of large L5B neurons might require functional
NMDA-Rs (Larkum et al., 2009), sodium channels (Magee and
Johnston, 1995), or calcium channels (Helmchen et al., 1999).
potentials with these channels intact (omitting TTX, CPP, and
4-AP from the bath) (Figures 6B and S6F). These measurements
were consistent with the sCRACM measurements. ChR2-photo-
stimulation-evoked responses were 6–7 times weaker in L5B
neurons compared to upper layer neurons recorded under iden-
tical conditions (p < 0.001, signed-rank test). The shapes of the
input maps were different under the two conditions, because,
in the absence of TTX, action potential propagation delocalizes
the effects of photostimulation (Petreanu et al., 2007, 2009).
These results support the conclusion that L5B cells, including
PT type neurons, receive little input from vS1 compared to
superficial vM1 neurons.
We note that the differences in vS1 input strength to L5B and
upper layer cells (L2/3, L5A) cannot be explained by the overlap
between vS1 axons and vM1 dendrites. Indeed, L5A neurons
received significantly more input from vS1 then L5B neurons,
even when normalized for dendritic length density (Figure S7).
Similar types of specificity have been reported in projections
from the thalamic PO nucleus to vS1 (Petreanu et al., 2009).
For comparison we provide this data (Figure S8). This confirms
Input L5A (pA)
Input L5B (pA)
Input L5A (pA)
Input L2/3 (pA)
L2/3 L5A L5B L6
Normalized vS1 input
Input L5A (pA)
Input L6 (pA)
Figure 4. Input from vS1 to vM1 as a Function of Layer
(A) Representative dendritic arbors in vM1, sorted by depth in the cortex.
(B) sCRACM input maps indifferentlayers. The maps werethresholded to show pixels withsignificant signal (ExperimentalProcedures). Notedifferencesincolor
(C–E)Comparison of input using L5A as the reference. A neuron in L2/3, L5B, or L6 was recorded in the same brain slice as a neuron in L5A. Input (summed pixels
with significant signal) for L2/3 (C) (n = 19 pairs of cells, 11 mice), L5B (D) (n = 31 pairs of cells, 15 mice), or L6 (E) (n = 21 pairs of cells, 8 mice) neurons is plotted
against input to L5A neurons. Statistics, signed-rank test.
(F) Summary of pair wise comparisons. The histogram corresponds to the slopes of the regression lines in (C)–(E).
See also Figure S6 and Table S1.
Neuronal Circuits between Sensory and Motor Cortex
116 Neuron 71, 111–123, October 6, 2011 ª2011 Elsevier Inc.
that geometric overlap is not an accurate predictor of the
strengths of functional projections (Brown and Hestrin, 2009;
Callaway, 2002; Shepherd et al., 2005).
vS1-Projecting Neurons in vM1 Receive Input from vS1
L2/3 and L5A neurons in vS1 provide input to L2/3 and L5A
neurons in vM1 (Figures S5A, S5B, and S9; Sato and Svoboda,
2010). Similarly, a subset of vM1 neurons, concentrated in L2/3
and L5A, connect with L2/3, L5A, and L5B neurons in vS1 (Pet-
reanu et al., 2009; Figures 2B and 2C). Do neurons in L2/3 and
L5A in vS1 and vM1 form a direct feedback loop? Or do L2/3
and 5A in vM1 harbor distinct set of neurons, one receiving input
guish between these possibilities wecoinjected virus expressing
ChR2-venus and retrogradely-transported microbeads into vS1
(Figure 7A). In vM1, the distribution of retrogradely labeled cells
overlapped with the band of axonal labeling (Figure 7B). The vast
majority ofbead-positive cells werelocated in L2/3and L5A(Fig-
ure 2C), similar to the neurons receiving strong input from vS1
(Figure 4). We measured sCRACM maps for bead-positive cells
and neighboring bead-negative cells (soma distance <50 mm,
without bias in vertical depth; Figures 7C–7E, S6G, and S6I).
Bead-positive vS1-projecting neurons received significantly
stronger (2.5-fold) input from vS1 than bead-negative neurons
(Figures 7E; p < 0.001, signed-rank test). Some bead-positive
cells were found (Figure 2C) and recorded in L5B (Figure S6C).
Similar to bead-positive cells in L2/3 and L5A, bead-positive
cells in L5B received stronger vS1 input comparable to neigh-
boring bead-negative cells (sub group in Figure 7E; p < 0.001,
signed-rank test); but the input was still much less than the input
to upper layer cells in the same column (Figure S6I; p < 0.001,
signed-rank test). We also performed the converse experiments,
recording in vS1 from vM1-projecting neurons and their neigh-
bors (Figure S9). Here, there was no difference between bead-
positive and bead-negative neurons (Figure S9G; p > 0.1,
signed-rank test). Thus, neurons in upper layers (L2/3 and L5A)
n = 16
n = 14
n = 17
Aligned by soma
n = 16
n = 14
n = 17
Aligned by pia
n = 30
n = 30
n = 14
Figure 5. Laminar Input to vM1 Neurons from vS1
(A) Averaged sCRACM input maps aligned by pia. Trian-
gles, soma locations (number of cells in each group are
noted in each panel; total n = 77 cells, 35 mice).
(B) Averaged sCRACM input maps aligned by soma
locations. Right, averaged dendritic length density as a
function of depth in the cortex (dendritic reconstructions
were performed for a subset of cells; L2/3, n = 7; L5A, n =
19; L5B, n = 15; L6, n = 5). The integral of the dendritic
density was normalized to 1.
See also Figure S6 and Table S1.
of vS1 and vM1 form a strong feedback loop.
Furthermore, within a layer, a neuron’s projec-
tion pattern can determine the strength of
specific types of input.
We used viral anterograde tracing, retrograde
circuitmapping todescribe thecircuitslinkingvS1(barrel cortex)
and pyramidal neurons in vM1 (vibrissal motor cortex). vS1
axons preferentially targeted upper layer (L2/3, L5A) neurons in
vM1 (Figure 4). vM1 neurons projecting back to vS1 received
particularly strong direct input from vS1 (Figure 7). vS1 input to
conspicuously avoided the majority of pyramidal tract (PT) type
neurons (Figure 6), despite pronounced overlap of dendrites
and axons. Our findings suggest that upper layers in vM1 partic-
ipate in forming sensorimotor associations (Figure 8).
AAV-Mediated Anterograde Tracing
For anterograde tracing we used AAV expressing GFP or the red
fluorescent protein tdTomato (Shaner et al., 2004) to infect
neurons invS1orvM1 (Figures1andS1; MovieS1).Ahigh-reso-
lution slide scanner was used to image fluorescent axons
throughout the brain (Supplemental Experimental Procedures).
Expression of the fluorescent proteins produced sufficient
contrast to detect and image individual axons in their projection
zones (Figures S1D and S1H), often millimeters from their parent
cell bodies (Aronoff et al., 2010; De Paola et al., 2006; Grinevich
et al., 2005; Petreanu et al., 2009; Stettler et al., 2006). This is
remarkable because these axons are the smallest structures in
the brain, often with diameters less than 100 nm (Shepherd
and Harris, 1998; De Paola et al., 2006). These images allowed
us to quantify the projection strength from vS1 and vM1 to
numerous areas throughout the brain. We confirmed previously
reported projections from the barrel cortex (for example, vS1 /
striatum, vM1, FrA, thalamus, S2), but we also found projections
to other areas (vS1 / orbital cortex, reuniens thalamic nucleus/
rhomboid thalamic nucleus, infralimbic cortex/dorsal pedun-
cular cortex, MS1, cMS1, LPtA). From the vibrissal motor cortex
strong projections included, vM1 / striatum, vS1, FrA, thal-
amus, contralateral vM1. Weaker projections included vM1 /
contralateral claustrum, which was previously described in rats
(Alloway et al., 2009). Quantification of the projection strength
Neuronal Circuits between Sensory and Motor Cortex
Neuron 71, 111–123, October 6, 2011 ª2011 Elsevier Inc. 117
tures (Figures 1C and 1H) serves to rank-order brain areas for
potential importance in vibrissa-dependent somatosensation
and functionalfollow-up experiments (Luoetal.,2008;O’Connor
et al., 2009).
Two caveats deserve discussion. First, our quantification of
projection strength is only indirectly related to synaptic output.
Fluorescence is proportional to axonal volume and since axonal
caliber is constant, also to axonal length density. For cortical
axons terminating within cortex bouton density is approximately
constant (Anderson et al., 2002), and most axonal length resides
in these termination zones; fluorescence is, therefore, expected
to be an accurate predictor of bouton number and output
strength. However, measurements of bouton densities in other
target areas are necessary to strengthen the interpretation of
projection strength based on fluorescence measurements.
Second, numerically small projections can be functionally prom-
inent, as has been documented for thalamocortical projections
to L4 in the sensory cortex (Benshalom and White, 1986; da
Costa and Martin, 2009).
Simultaneous tracing with pairs of colors (Figures 1E and S3)
confirmed that the vS1 / vM1 projection is topographic (Hoffer
et al., 2005; Welker et al., 1988). Furthermore, the projection
splits into multiple domains (Figure 1E3). Additional experiments
are required to determine if vibrissal motor cortex contains
multiple motor maps (Tennant et al., 2011). The more caudal
domain overlaps with the posterior-medial domain of the tongue
motor cortex (Komiyama et al., 2010).
The Circuits Connecting vS1 and vM1
cells, defined groups of neurons, and brain areas. At the highest
level, the hierarchical organization of brain areas has long been
a cornerstone in our understanding of the mammalian nervous
system (Felleman and Van Essen, 1991; Kleinfeld et al., 1999;
Sporns and Ko ¨tter, 2004). However, each brain area itself
local circuits (Binzegger et al., 2004; Hooks et al., 2011; Lefort
et al., 2009). Subcellular ChR2-assisted circuit mapping
(sCRACM) allows long-range connections between brain areas
to be linked to defined neuronal populations within the local
circuits (Petreanu et al., 2007, 2009).
sCRACM has limitations. First, the detailed mechanisms
driving neurotransmitter release evoked by ChR2 may not be
the same as when evoked by action potentials (Zhang and Oert-
ner, 2007). However, our results were quantitatively similar with
action potentials blocked or intact (Figure 6), suggesting that
ChR2-based mapping provides accurate measurements of
relative input strength. Second, synaptic currents recorded at
the soma can be greatly attenuated by electrotonic filtering in
the dendrites. More distal inputs are therefore underrepresented
in a sCRACM map. Third, axonal expression levels of ChR2
typically vary greatly across experiments. Comparison of input
normalization of input strength within single experiments.
We mapped the long-range connections between sensory
andmotorareas involvedinwhisker-based sensation.
Figure 6. Low Input to Brainstem-Projecting L5B Pyramidal Neurons from vS1
(A) Input to upper layer neurons (L2/3 and L5A) compared to L5B neurons (left, actual values; right, normalized) (n = 36 pairs of cells, 17 mice). Statistics, signed-
rank test. The circle in the right panel indicates the mean (0.18).
(B) Same experiments as (A), except without antagonist cocktails (CPP, TTX, and 4-AP) (n = 23 pairs of cells, 4 mice). Statistics, signed-rank test. The circle in the
right panel indicates the mean (0.26).
(C and D) Input to upper layer neurons (L2/3 and L5A) compared to brainstem-projecting L5B neurons. (C) Individual maps of a L5A cell (left) and a bead-positive
L5B cell (middle). Triangles indicate the soma locations. Both maps were obtained under identical experimental conditions in the same brain slice. An overlay
of DIC and red fluorescence shows a bead-positive L5B cell (right). (D) Input to upper layer neurons (L2/3 and L5A) compared to bead-positive L5B neurons.
(left, actual values; right, normalized) (n = 8 pairs of cells, 5 mice). Statistics, signed-rank test. The circle in the right panel indicates the mean (0.28).
See also Figures S5–S8 and Table S1.
Neuronal Circuits between Sensory and Motor Cortex
118 Neuron 71, 111–123, October 6, 2011 ª2011 Elsevier Inc.
Somatosensation relies on active movement of whiskers to
gather information in the vicinity of the head. Sensory input is
critical for object localization and recognition, and also to guide
future movements of the whiskers. By collating our studies of
long-range connections with previous data on thalamocortical
(Bureau et al., 2006; Lu and Lin, 1993; Meyer et al., 2010b; Pet-
reanu et al., 2009) and local cortical circuits (Hooks et al., 2011;
Lefort et al., 2009; Svoboda et al., 2010) it is possible to sketch
out a circuit diagram for the cortical vibrissal sensorimotor loop
in mice (Figure 8).
Forces acting on whiskers excite sensory neurons in the
trigeminal ganglion, triggering activity which ascends through
the brainstem into VPM and L4 neurons in the barrel cortex (Pe-
L2/3neurons, whichinturnexciteneuronsin L5AandalsoinL5B
(Armstrong-James and Fox, 1987; Brecht et al., 2003; Brecht
and Sakmann, 2002; Hooks et al., 2011; Lefort et al., 2009;
Manns et al., 2004). A subset of L2/3 and L5A neurons project
to vM1 (Figures S5A, S5B, and S9C), where they strongly target
upper layer neurons in L2/3 and L5A, and only weakly deep layer
neurons in L5B and L6 (Figures 4C–4F, 6, and S6). Upper layer
neurons in vM1 receiving strong input from vS1 project back to
vS1 (Figures 2B, 2C and 7B), where they synapse onto neurons
in L2/3, L5A, and L5B (Petreanu et al., 2009). Cortico-cortical
neurons in L2/3 and L5A in vM1 are thus the nexus of a powerful
disynaptic feedback loop (vS1, L2/3/5A ) / vM1, L2/3/5A),
linking sensory and motor cortex (Figure 8). This loop apparently
violates the no-strong-loops principle which is thought to govern
inter-areal connectivity in the visual system (Crick and Koch,
additional experiments are required to determine the separate
contributions of L2/3 and L5A neurons to activating targets in
vM1 (Aronoff et al., 2010). A small subset of deep L6 cells in
vS1 also projected to vM1 (Figures S5A, S5B, and S9C). These
neurons were only sparsely infected by the AAV virus, and their
contribution to the vS1 / vM1 projection, although likely small
in total, was underrepresented in our study.
Microbeads in vM1
vS1 axons in vM1
Figure 7. vS1-Projecting Neurons in vM1 Receive Strong Input from vS1
(A) Schematic of theexperiment.AAV-ChR2-venus (green) and fluorescent microbeads (red) werecoinjected invS1. Recordings were made invM1 (dashedline).
(B) Representative images of vS1 axons (left), bead-labeled cells (vS1-projecting cells; middle), and the overlay (right) in vM1.
(C) Example sCRACM input map recorded in a retrograde bead-positive cell (triangle, soma location).
(D)AveragesCRACMmaps for bead-positiveL2/3neurons (left)aligned onthe pia (n= 7cells, 6mice) and forbead-positive L5A neurons (right) alignedonthe pia
(n = 8 cells, 6 mice).
rank test. The circle in the right panel indicates the mean (0.40).
See also Figures S6 and S9 and Table S1.
Figure 8. The Long-Range Circuits Connecting vS1 and vM1
Red, projections from vS1 to vM1. Blue, projections from vM1 to vS1. Gray,
three strongest intracortical projections. Line thickness is proportional to the
strength of connection strength. Targets of vM1 projections: zona inserta
(ZI, magenta), superior colliculus (SC, cyan), braisnstem (BS, green), and
posterior thalamic nucleus (PO, blue).
Neuronal Circuits between Sensory and Motor Cortex
Neuron 71, 111–123, October 6, 2011 ª2011 Elsevier Inc. 119
deep layer output neurons in vM1? The local circuit in somatic
shows a top-to-bottom organization. Interlaminar excitation is
strongest from superficial layers downward, with a powerful de-
scending projection from L2/3 to the border of L5A and L5B
(Hooks et al., 2011). Weaker projections exist from L5A to L5B.
Similarly, L2/3 and/or L5A neurons in vM1 excite L5B neurons
in vS1 (Petreanu et al., 2009). L5B neurons in vM1 (Figures 2
and S5D) and vS1 (Matyas et al., 2010) are projecting to motor
centers in the brainstem. Our studies thus suggest that sensori-
motor integration underlying adaptive whisking occurs primarily
in the superficial layers, and the results of this computation are
then passed on to neurons in deeper layers, which control motor
centers (Fetz and Baker, 1973; Matyas et al., 2010).
PT type neurons in L5B of vM1 primarily control whisker
protractions, whereas PT type neurons in L5B of vS1 might
control whisker retractions (Matyas et al., 2010). Our studies
suggest that whisker retractions triggered by intracortical micro-
stimulation in vM1 are mediated by direct stimulation of cortico-
cortical neuronsinL2/3 andL5A,whichin turnexcitedeeplayers
in vS1 (Petreanu et al., 2009).
The documented sources of synaptic input to deep neurons in
vM1, including PT type neurons, remain few and weak (Hooks
et al., 2011; Anderson et al., 2010; Figures 4 and 6). L5B and L6
neurons receive only weak input from superficial layers (Hooks
et al., 2011; Anderson et al., 2010) and from vS1 (Figures 4 and
for the input to PT type neurons in vM1.
Specificity in Long-Range Projections
Numerous experiments using a variety of techniques have
shown that the overlap of axons and dendrites fails to accurately
predict the strengths of connections between neuronal popula-
tions (Callaway, 2002; White, 2002). For example, in vS1, L4
neurons strongly excite L2/3 pyramidal cells, but not inter-
mingled somatostatin-positive interneurons (Dantzker and
Callaway, 2000). In the rat vS1 but not in the mouse (Bureau
et al., 2006), L2/3 pyramidal cells above barrels are strongly
excited by L4 neurons, whereas L2/3 pyramidal cells above
septa receive only weak input (Shepherd et al., 2003; Shepherd
and Svoboda, 2005). In mouse vS1, L5A neurons receive strong
not (Petreanu et al., 2009; Figure S8). Similarly, in the mouse
vM1, L5A neurons receive strong input from vS1 compared to
L5B neurons (Figures 3D, 4B–4F, 6, and S7). Input strength
can also depend on the neuron’s projection target (Figure 7; An-
derson et al., 2010). Specificity beyond structure also exists at
the level of subcellular distributions of synapses. For example,
L6 neurons in vM1 receive input mainly on their sparse apical
dendrite, and little input on their basal dendrites (Figures 4B4
and 5B4). These findings highlight the need for methods of
circuit-mapping that detect functional synapses.
Mice whisk in an adaptive manner to extract information about
the tactile world. For example, in object localization tasks
rodents move their whiskers to locate an object in the vicinity
of their heads (Knutsen et al., 2006; Mehta et al., 2007; O’Connor
et al., 2010a). Here, a sensory cue (typically visual or auditory)
triggers a motor program which leads to contact between
whisker andobject. Thesensory input in turnchanges thewhisk-
ing pattern (Mitchinson et al., 2007; O’Connor et al., 2010a).
Ultimately the animal makes a judgment about object location
to collect a reward by executing a second motor program
involving licking. Astandardlaboratory task ofthistype therefore
involves multiple stimulus-response associations (Lalazar and
Vaadia, 2008). The microcircuitry connecting sensory and motor
cortices described here might help to implement these stimulus-
It has been suggested that vibrissa-based object localization
requires the brain to interpret contact between whisker and
object in the context of an internal reference signal indicating
whisker location or phase (Curtis and Kleinfeld, 2009; Diamond
et al., 2008). This reference signal might consist of an efference
copy generated by the inverse model driving goal-directed
whisking. The circuits uncovered here may underlie mixing of
whisking and contact signals and thus, might underlie computa-
tion of object location.
Experiments were conducted according to National Institutes of Health guide-
lines for animal research and were approved by the Institutional Animal Care
and Use Committee at Janelia Farm Research Campus. For anterograde
tracing we used adeno-associated virus (AAV; serotype 2/1) expressing
eGFP (www.addgene.com) or tdTomato (a gift from J. Magee) under the
CAG promoter. For sCRACM mapping experiments, we used AAV virus (sero-
type 2/1; in some experiments serotype 2/10) expressing either ChR2-venus
tracing we used fluorescent LumaFluor microbeads (LumaFluor Inc.). C57BL/
6J mice (Charles River) (13–16 days old) were anesthetized using an isoflur-
ane-oxygen mixture and placed in a custom stereotactic apparatus. A small
hole was drilled into the skull, allowing insertion of a pulled glass pipette
(Drummond) (tip diameter: 10–20 mm for virus; 40–60 mm for LumaFluor
microbeads). For sCRACM experiments, coordinates were as follows (in mm,
from bregma): vS1, 0.5 to 0.8 posterior, 2.9–3.3 lateral; vM1, 1.0?1.1 anterior,
ysis (Figures 1B, 3, 4, 5, 6, 7, and S1B–S1H). See Supplemental Experimental
Procedures for further details.
Slice Preparation and Electrophysiology
Brain slices were prepared as described (Bureau et al., 2006) 14 to 24 days
after viral infections (see Supplemental Experimental Procedures). For vM1,
of apical dendrites with the slice surface. When cutting from rostral to caudal,
1?2 slices, ?0.8–1.3 mm anterior to bregma, corresponding to the first and/or
second slice containing a fused corpus callosum, were used. For vS1 slices,
the brain was cut in the coronal plane. Only slices with prominent barrels
(Figure S9B) were used (Petreanu et al., 2009).
All recordings were performed at room temperature in circulating ACSF.
For most experiments (except Figures 6B, S6F, S8B, and S8C) TTX
(1 mM), 4-AP (100 mM), and CPP (5 mM) were added (Petreanu et al., 2009).
Whole-cell recordings were obtained using borosilicate pipettes (resistance
4–6 MU) and an Axopatch 700B amplifier (Axon Instruments). The intracellular
solution contained (in mM): 128 potassium gluconate, 4 MgCl2, 10 HEPES,
1 EGTA, 4 Na2ATP, 0.4 Na2GTP, 10 sodium phosphocreatine, 3 sodium
L-ascorbate, and 0.02 Alexa-594 (Molecular Probes), and 3 mg/ml biocytin
(pH 7.27; 287 mOsm). Cells were recorded at depths from 46 to 103 mm
Neuronal Circuits between Sensory and Motor Cortex
120 Neuron 71, 111–123, October 6, 2011 ª2011 Elsevier Inc.
within the brain slice. Data were acquired using Ephus (www.ephus.org).
Pyramidal neurons were selected based on their morphology confirmed
under fluorescence microscopy (Alexa-594 in pipette solution) or post hoc
by biocytin staining. For sCRACM mapping, EPSC were recorded in voltage
clamp while holding at ?70 mV (L2/3 cells) or ?75 mV (L5 cells). Access
resistances ranged 10–40 MU. For every vM1 cell included in the data set,
the site of viral infection was confirmed to lie within the barrel cortex by post
hoc histological analysis. Most infections were roughly centered on the barrel
The position of a blue laser beam (473 nm; Crystal Laser) was controlled with
galvanometer scanners (Cambridge Scanning, Inc.). The beam passed
through an air objective (43; 0.16 NA; UPlanApo, Olympus) and was nearly
cylindrical (?8–16 mm in diameter, full-width at half max at the specimen
plane). The light pulses were controlled with a Pockels cell (ConOptics). The
power (0.7–1.8 mW) of the light pulses (duration, 1–2 ms) was adjusted so
that the largest EPSCsCRACMhad peak values in the range of 50–100 pA; in
some cases EPSCsCRACMwere smaller even at the highest laser powers.
Each trial consisted of approximately 100 ms baseline, the photostimulus,
and300msresponse period. Stimulationsiteswereona50mmgrid.Gridsizes
(12324, 123 26or 123 28)wereadjustedbased onthe sizeof theneuron;all
grids covered all potential sites of input within the dendritic arbor. Each map
was repeated 2–4 times. The laser stimuli were given in a spatial sequence
designed to maximize the intervals between stimuli arriving to neighboring
spots (Shepherd et al., 2003).
sCRACM pixel values corresponded to the mean EPSC amplitude in a 75 ms
time window after the onset of the stimulus (given in picoamperes, pA, for
consistency with previous studies). In some figure panels (Figures 3D and
4B), we display only pixels with significant responses (response amplitude
>63 standard deviation of the baseline). For each cell, maps were averaged
across repeats. To show the spatial distribution of input, maps were first
peak-normalized (Figures 5,7D,S9E, and S9F) and then averaged acrosscells
within a class. Normalization was necessary because response amplitudes
vary across experiments depending on the infection efficiency and the ChR2
To quantify the total input for pairs of neighboring neurons we summed all
pixels that showed significant responses (>63 standard deviation of the base-
line; Figures 3D, 4C–4F, 6, 7E, S8D, and S8E). Only cell pairs with soma
distance %300 mm and dendritic overlap were used. We performed additional
analyses to check for possible biases imposed by thresholding (>63 standard
deviation of the baseline): First, we computed input across a 3 3 3 grid around
the soma (Figures S6D–S6F). Second, we generated a mask by averaging
responses (>53 standard deviation). The mask was then used to compute
input from the original maps (Figures S6G–S6I). Third, we also computed the
mean pixel value over the entire map without thresholding (data not shown).
These three analysis methods yielded consistent results. Since the time
between stimulus and the beginning of the baseline period for the next trial
was fairly short (300 ms), we corrected for bleedthrough across trials (baseline
drift). Becausethe grid size for stimulation was always larger than the dendritic
arbors of the recorded cells (for example, Figure 3B), we estimated the base-
line drift from the traces far outside the cell’s dendritic arbor (these traces were
‘‘blanks’’ that could not have contained true responses; they thus represent
pure baseline drift). We then subtracted the baseline drift from the mean value
of all other traces.
Paired comparisons used the nonparametric Wilcoxon signed-rank test
(Figures 6, 7, S6, S7, and S9).
Supplemental Information includes nine figures, one table, one movie, and
supplemental text and can be found with this article online at doi:10.1016/
This work was funded by the Howard Hughes Medical Institute. We thank
Gordon Shepherd for advice and extensive discussions; Asaf Keller for advice
on electrical microstimulation in vM1; Tim O’Connor for programming; Brenda
Shields, Amy Hu, Alma Arnold, and Kevin McGowan for technical support;
Takashi Sato and Haining Zhong for help with experiments and analysis;
Stefanie Kaech Petrie for help with the blind retrograde beads counting; and
Diego Gutnisky and Zengcai Guo for comments on the manuscript.
Accepted: July 29, 2011
Published: October 5, 2011
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