A considerable number of axons from neurons in one cortical area end up on other cortical
areas. When one neuron in one cortical area sends an action potential to target neurons
in other cortical areas, this is a realization of a cortico-cortical communication.
Sensory perception, thinking, and planning of a specific behavior, all rely on the
evolution of cortico-cortical communications. The action potentials change the membrane
potentials in the target neurons and, in turn, may excite these neurons to produce
action potentials and complex patterns of excitation and inhibition in their targets.
We launched the special research topic of cortico-cortical communication dynamics
to invite contributions that would cast light on such evolution of spatio-temporal
action potential and membrane potential dynamics in the cerebral cortex.
The contributions were theoretical models, human EEG, and MEG data and data-driven
models, and in vivo experimental data from animals accounting for specific aspects
of cortico-cortical communication dynamics.
In a recent in vitro experiment, Branco et al. (2010) show that single dendrites of
pyramidal layer 2–3 neurons depolarize more and have larger Ca2+ influx when their
depolarization progresses toward the soma, than when depolarization progresses away
from the soma. Kiebel and Friston (2011) construct a (developmental) model of the
pruning of single synapses and show that they can reproduce the findings of Branco
et al. (2010) if the self-organizing pruning follows a Bayesian and information theory
derived principle of minimization of free energy. Cortico-cortical communication dynamics
can only be comprehensively studied in vivo. In vivo, the neurons and their dendrites
are in a high conductance state (Destexhe et al., 2003), and the propagation of depolarizations
to the soma and action potential generation may thus be difficult to predict (Williams
and Mitchell, 2008). This does not exclude, however, that the model of Kiebel and
Friston (2011) may be appropriate in early development and in the formation of cortio-cortical
synapses. The pruning of synapses under development and hence the formation of the
adult cortical network is the theme of the contribution of van den Bergh et al. (2012).
Their model departs from a random network. This network is subsequently shaped by
spontaneous ongoing spike activity. After a while the random structure disappears
and many small-world sub-networks emerge. As van den Bergh et al. (2012) show, this
only happens if the connectivity in the network is larger than a critical value. This
is interesting as the developing brain has many cortico-cortical connections that
disappear at later stages.
As pointed out in a critical review of cortico-cortical communication dynamics, there
are many obstacles precluding the tracing the ms by ms evolution of the spatio-temporal
dynamics of the cortex (Roland et al., 2014). Therefore examination of the spatio-temporal
dynamics in biologically plausible computational models of neurons may be one way
to develop experimentally testable hypotheses. Li and Zhou (2011) made a computational
model of neurons in two inter-connected cortical areas. The duration of the delays
in communication and the distribution of inhibition in the local network determined
whether the neurons would spike in phase or in anti-phase and whether interactions
between slow and fast membrane oscillations would produce anti-phase spiking. These
findings are pertinent for the hypothesis on cortico-cortical communication through
coherence (Fries, 2009).
Facing the obstacles of tracing the spatio-temporal dynamics of cortico-cortical communications
at the cellular scale, many scientists choose to study membrane electrical activity
at the scale of large neuron populations, and from EEG and MEG signals try to infer
putative routes of communication. Banerjee et al. (2012) discuss these methods and
point out that there is no consensus as to what constitutes a large-scale network.
Further, they show how MEG measurements may be interpreted by combining the empirical
analysis with large-scale models of biologically realistic membrane activity. This
is what is done in the contributions by Misic et al. (2011) and Vakorin et al. (2011).
Their results show that time delays and the number of connections between sources,
of MEG signals or EEG signals, contribute to the relation between variance in the
signals and information transfer between the sources (Misic et al., 2011; Vakorin
et al., 2011).
At the mesoscopic scale one can observe changes in the membrane potentials with voltage
sensitive dyes, local field potentials and combine this with recordings of action
potentials from a few neurons or single neurons in experimental animals. Harvey and
Roland (2013) demonstrate both forward spatiotemporal population membrane dynamics
in higher visual areas that after 50 ms was followed by backward propagation of net-excitation
from these areas in experiments with objects moving in the visual field. Vinnik et
al. (2012) examined the communications from the auditory cortex to the hippocampus
and show that the access to fire hippocampal neurons is state dependent. Sleep favors
fast reactions of the hippocampal neurons to the extent as only seen for novel sounds
in awake animals (Vinnik et al., 2012). Civillico and Contreras (2012) examined how
the communication from the thalamus to the barrel cortex is affected by the state
of the neurons in the barrel cortex. When the cortical neurons were in an up-state,
the local field potentials, the membrane potential increases, and the multiunit activity
evoked by a whisker stimulus was smaller than when the whisker stimulus was given
just during the early transition from a down-state to an up-state (Civillico and Contreras,
2012).
If one wants to understand how the cerebral cortex works one must be able to trace
the evolution of the spatio-temporal transmission of action potentials and membrane
conductances down to the cellular scale. As the critical review concludes, this is
not possible yet. Assume that a full connectome of the mouse cerebral cortex exists
(Bohland et al., 2009). This might help in finding the target neurons in other areas
for a given neuron. However, it still remains to identify that source neuron spiking
in an experiment and measure the membrane potential changes induced by that neuron
on each of the target neurons, as each target neuron may have 1000 other source neurons.
One may argue that if this multidimensional cellular dynamics should have any impact
on perception and behavior, the dynamics of action potentials and membrane potential
dynamics at more coarse scales should organize to make such impacts. The contributions
to this special issue are fine examples of the many contemporary attempts to advance
theoretical knowledge of cortico-cortical communication dynamics, provide testable
hypotheses in this field, and test these hypotheses at the microscopic, mesoscopic,
and macroscopic scales.
Conflict of interest statement
The authors declare that the research was conducted in the absence of any commercial
or financial relationships that could be construed as a potential conflict of interest.