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CC COMMENTARY
Intrinsic Signals and Functional Brain
Mapping: Caution, Blood Vessels at Work
Costantino Iadecola
It has long been thought that there is a close relationship
between brain activity and cerebral blood f low [reviewed by
Raichle (Raichle, 1998)]. While in 1890 Roy and Sherrington
proposed the concept of an ‘intrinsic mechanisms’ responsible
for coupling neural activity to blood f low (Roy and Sherrington,
1890), more than a decade earlier the Italian physiologist Angelo
Mosso was already undertaking a detailed study of the changes in
cerebral hemodynamics associated with various psychological
states in humans (Mosso, 1881). Following up on these
pioneering efforts, our understanding of the localization of brain
function has advanced considerably thanks to techniques that
detect the changes in brain blood f low associated with brain
activity (Table 1). One of the most recent approaches is based on
monitoring activity-induced increases in cerebral oxygenation.
During functional activation cerebral blood f low increases more
than the oxygen demands of the brain (Fox and Raichle, 1986),
and such mismatch results in an increase in oxyhemoglobin and
a decrease in deoxyhemoglobin (Raichle, 1998). Activityinduced increases in brain oxygenation can be detected either
by magnetic resonance imaging (MRI), as blood oxygenation
level dependent (BOLD) contrast (Ogawa et al., 1992), or, by
optical imaging, as ‘intrinsic signals’ (Grinvald et al., 1986).
Because of the importance and widespread use of these
approaches in functional brain mapping, there is a great interest
in elucidating the precise mechanisms by which these signals are
generated and how accurately they ref lect brain activity
(Raichle, 1998).
In the present issue of Cerebral Cortex, Harrison and
colleagues (Harrison et al., 2002) provide a much-needed piece
of information concerning the relationship between intrinsic
signals and cerebral vasculature. These authors used optical
imaging to investigate the intrinsic signals evoked by auditory
stimuli in the auditory cortex of the chinchilla. The spatial
distribution of the signals was then correlated with the distribution of cerebral blood vessels, visualized in the same animal post
mortem by corrosion casts. Through this careful analysis they
were able to determine that the area in which intrinsic signals
are detected overlaps remarkably well with the distribution
of cerebral blood vessels supplying the activated region. Thus,
signals emanated only from areas endowed with a rich vascular
network, and no signals were obtained from adjacent regions in
which the vasculature was less dense. Although neural activity
was not mapped in the same animals in which the optical
recordings and vascular casts were obtained, a map correlating
unit activity with intrinsic signals in separate animals revealed
that there was a general correspondence between active sites
and location of the intrinsic signals. However, in some cases unit
activity was not detected in areas in which intrinsic signals were
generated. They also found that the cerebral vasculature is
endowed with sphincter-like structures, often strategically
placed at arteriolar branch points. The authors argue that these
structures are involved in controlling the local distribution of
f low within the vascular network.
These findings have notable implications for functional brain
mapping using hemodynamic changes as a ‘proxy’ for neural
activity. On the one hand, the finding that intrinsic signals
identif y reasonably well the area of activation, assessed by
electrophysiological recordings, supports the validity of using
vascular-based methods to localize brain function. On the other
hand, the observation that the topography of the intrinsic signals
overlaps with the distribution of cerebral blood vessels within
the activated region suggests that the vascular geometry of a
brain region dictates the spatial distribution of these signals.
Therefore, depending on the spatial relationships between
vascular network and active neurons, there might be instances
in which the area of activation will not match the area from
which the signals are generated. This point is demonstrated by
the data of Harrison et al. (Fig. 2) showing that intrinsic signals
can be detected from areas in which there is no evoked neural
activity. Although in some areas vascular and neural architecture
are well matched, e.g. in the rodent whisker–barrel cortex
(Woolsey et al., 1996), this correspondence cannot be assumed
to occur in all brain regions and for all activation paradigms.
Another factor that may prevent complete overlap between
vascular and activity maps is that the vascular dilatation
responsible for the increase in blood f low evoked by neural
activity is propagated in a retrograde fashion to upstream
arterioles located outside the activated area (Iadecola et al.,
1997). This phenomenon, termed retrograde vasodilation,
serves the purpose of dilating upstream arterioles that are
critical for regional f low control. Therefore, during functional
activation, an increase in f low is observed also in remote regions
in which no neural activity can be detected.
Another implication of the data of Harrison et al. is that the
intensity of the intrinsic signals generated from a brain region
depends on local vascular density. Therefore, given an equal
degree of neural activation, the area in which vascular density is
more sparse will generate a less robust intrinsic signal. Consequently, the ‘hot spots’ on a functional map may not necessarily
indicate the areas that are most active in the execution of a
specific task. While Harrison et al. focused on the relationship
between intrinsic signals and vascular networks, Logothetis and
colleagues investigated the specific components of the neural
activity linked to the vascular signal (Logothetis et al., 2001).
These authors recorded simultaneously electrophysiological
parameters and BOLD fMRI in the monkey visual cortex and
found that field potentials, rather than spiking activity, best
predicted the vascular signal. This finding suggests that neural
input and local processing, rather than neural output, are
the most important determinants of the vascular change, a
conclusion reached also by others on the basis of direct
f low measurements in cerebellum (Mathiesen et al., 1998).
© Oxford University Press 2002. All rights reserved.
Cerebral Cortex Mar 2002;12:223–224; 1047–3211/02/$4.00
Department of Neurology, University of Minnesota,
Minneapolis, MN 55455, USA
Table 1
Historical overview of activity-induced cerebrovascular changes in the human brain
Authors
Finding
Technique
(Mosso, 1881)
(Fulton, 1928)
(Kety, 1950)
Increased brain volume during mental processing
Increased flow turbulence in occipital cortex during visual stimulation
Increase in flow and cerebral metabolic rate for oxygen during anxiety
(Ingvar and Risberg, 1967)
(Fox and Raichle, 1986)
Increased cerebral blood flow in speech-related areas during word repetition
Sensory stimulation increases blood flow in somatosensory cortex out of proportion to
oxygen use
Increased blood volume in visual cortex during photic stimulation
Increased blood oxygenation level dependent (BOLD) contrast in visual cortex during
photic stimulation
Monitoring of intracranial pressure through a breach in the skull
Recording of bruit from vascular malformation in occipital cortex
Cerebral artero-venous difference of inhaled nitrous oxide (Kety and Schmidt
method)
Regional brain clearance of 133Xe injected into the carotid artery
Positron emission tomography using 15O water as a tracer
(Belliveau et al., 1991)
(Ogawa et al., 1992)
Logothetis and colleagues also point out that, due to its higher
signal-to-noise ratio, neural activity can be present in areas in
which no BOLD contrast is detected, resulting in underestimation of activated areas assessed by fMRI. This conclusion
also suggests caution in the functional interpretation of activity
maps based exclusively on the presence or absence of the BOLD
signal.
The finding that there might be sphincter-like structures
capable of controlling the distribution of f low within the
cerebral microvascular network is also of interest, and its
significance has to be discussed in the context of a large body of
work suggesting that cerebral blood vessels receive neural
projections from intrinsic neurons (Eckenstein and Baughman,
1984; Vaucher and Hamel, 1995; Krimer et al., 1998). It is
tempting to speculate that these sphincter-like structures are
controlled by neural projections originating from neurons
dedicated to f low regulation. Such neurovascular units would be
well suited to control the timing and spatial distribution of the
increases in f low evoked by neural activity, and could regulate
f low for purposes other than to support the changing energetic
needs of the tissue. For example, these neural networks could
mediate anticipatory increases in blood f low in preparation for,
rather than in response to, an increase in energy demands. Such
anticipatory neurovascular control could, perhaps, explain why
during activation the increase in cerebral blood f low greatly
exceeds the oxygen needs of the tissue. This hypothesis,
however, awaits experimental confirmation.
Notes
Address correspondence to Costantino Iadecola, Department of
Neurology, University of Minnesota, 516 Delaware Street SE, Minneapolis,
MN 55455, USA.Email: [email protected].
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