How silent is the brain: is there a “dark matter” problem in neuroscience?

Abstract

Evidence from a variety of recording methods suggests that many areas of the brain are far more sparsely active than commonly thought. Here, we review experimental findings pointing to the existence of neurons which fire action potentials rarely or only to very specific stimuli. Because such neurons would be difficult to detect with the most common method of monitoring neural activity in vivo-extracellular electrode recording-they could be referred to as "dark neurons," in analogy to the astrophysical observation that much of the matter in the universe is undetectable, or dark. In addition to discussing the evidence for largely silent neurons, we review technical advances that will ultimately answer the question: how silent is the brain?

Cholinergic filtering in the recurrent excitatory microcircuit of cortical layer 4

“…S3.). Thus, because i) it is unlikely that volume transmission of ACH reaches concentrations in the millimolar range in vivo, ii) both the spontaneous and sensoryevoked spiking activity of S1 PCs in vivo are low (36)(37)(38), iii) only less than half the PCs are transiently hyperpolarized, and iv) the transient hyperpolarization represents only a minor part of the biphasic effect of ACH (Ϸ2.4% of total duration in L5, Ϸ5.2% in L2/3; Ϸ21% of peak depolarization in L5, Ϸ45% in L2/3), we conclude that the effect of ACH is predominantly excitatory in L2/3 and L5 of S1. The presence of a different mACHR subtype in L4-SNs than in the L2/3 and L5 PCs further supports the idea of a layerspecific effect of ACH.…”

Instabilities in attractor networks with fast synaptic fluctuations and partial updating of the neurons activity

“…There is no input on the other 1 − ρ, so that information from the previous state is maintained, which was argued to be a basis for working memories (Egorov et al, 2002;LeBeau et al, 2005). On the other hand, varying ρ may also be relevant to simulate various situations of persistent activity (Wagenaar et al, 2006), the observed variability of the neurons threshold (Azouz and Gray, 2000), and the possible existence of silent neurons (Olshausen and Field, 2004;Shoham et al, 2006), for instance.…”

What we can do and what we cannot do with fMRI

“…The strong selection bias during extracellular recordings is partly due to practical limitations (for example, injury or simply size bias 62 ) and partly to the physiological properties of neurons and/or the organizational principles of neural networks. In fact, many different types of electrical and optical measurements provide evidence that a substantial proportion of neurons, including the cortical pyramidal cells, might be silent 63 . Their silence might reflect unusually high input selectivity or the existence of decoding schemes relying on infrequent co-spiking of neuronal subsets.…”