Intracellular and computational evidence for a dominant role of internal network activity in cortical computations
Highlights
► The brain displays considerable spontaneous activity. ► Neurons do not respond only to external inputs, but the response is also a function of the spontaneous activity. ► The paper reviews intracellular and modeling evidence for this phenomenon. ► A scheme is proposed to reconcile apparently conflicting results. ► It is concluded that spontaneous activity should be an integral part of brain computations.
Section snippets
The intrinsic activity of the brain
The first proposal that neurons are not passive relays being driven by external inputs dates back to the early 20th century with the Belgian electrophysiologist Frederic Bremer [16••, 17]. He proposed that neurons generate intrinsic and self-sustained activity under the form of intrinsic oscillatory properties. The current thinking at the time was that oscillatory activity arises from circulating waves of activity, a theory called the ‘circus movement theory’. Bremer was an opponent to this
Is there quiescence in the absence of input?
Although such findings offer a nice perspective to explain population recordings, they are not consistent with all of the available experimental data. In particular, in the primary visual cortex (V1), a large number of studies have demonstrated clear visual responses and selectivity of neurons to features such as orientation, direction, and contract [29]. Not much spontaneous activity seems to be present in such single-cell experiments (see also [30]). Very low levels of spontaneous activity
Intracellular and computational evidence for dominant internal dynamics
Another set of evidence is provided by model-based analyses of intracellular recordings in vivo. Figure 2a shows examples of intracellular recordings of cat V1 neurons during spontaneous activity (SA) and the presentation of natural images (NI) [35] (original data from [36]). To measure statistical similarity, the frequency scaling exponent was computed from the power spectrum of the signals (Figure 2b), yielding exponent values for different stimulus conditions. Remarkably, the exponents were
Proposed scheme to account for the different experiments
To account for the disparity of the above results, a simple model of a neuron receiving two input sources was simulated. First an ‘intrinsic activity’ consisting of stochastic release at excitatory and inhibitory synapses, and second, an ‘external input’ consisting of a controlled stimulation of an independent set of excitatory and inhibitory synapses (see scheme in Figure 5). For weak external inputs, the activity is dominated by intrinsic activity and one recovers the pattern of opposite
Conclusions
In summary, the intracellular and computational results reviewed here collectively suggest that the spike-triggered conductance patterns is a very powerful way to determine whether a system is dominated by its internal activity, or is driven by afferent activity, as summarized in Figure 5. This approach makes a number of predictions, which are briefly discussed here.
First, it suggests that in many sensory systems, the measurements reporting a concerted conductance increase can be explained
References and recommended reading
Papers of particular interest, published within the period of review, have been highlighted as:
• of special interest
•• of outstanding interest
Acknowledgements
Thanks to Thierry Bal, Olivier Marre, Cyril Monier, Zuzanna Piwkowska, Igor Timofeev, and Yves Frégnac for sharing experimental data, and all members of the UNIC for continuing support. This work has been supported by the CNRS, the Agence Nationale de la Recherche (ANR HR-Cortex) and the European Community (FET grants FACETS FP6-015879, BRAINSCALES FP7-269921).
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