REVIEWS NATUREIVol 453112 June 2008 and in the (see 'Neural signals in Supplem d b ker microe trodes.The acellular field potentia captures at leas nce of NBR and de ns n minant neuronal n an electrode tip, on bet eld potentia Multiple ur activity and local fiel conclusions ot be yo tial data indicating that such ormation beta integrative soma nt hat all to th 8u时 hange in the powe ENy ban r tha excitatory input area o indi co sumption depending on th ontribution of the afor this case i Last but not inte ntribute alter CBF in respons may occasionally act as 'shunts'for the ry int sm nined se eparately,local spiking of the pes ofe to n erim ding toad ElctiophysiologcadlstudisCaminingtcndinidualcontr corti al output through the a ngof individual 6 other ty ct the the d it tothe direc f the lat d micro in the visual g rather than m dal cell ou of this fact,the nture of the EIN that s action and it han n was not the degre Icorrelates of the BOLD signa the the bution of any type any given time are conidered to mic resp current sink,w C2008 Macmillan Publishers Limited.All rights reservedIn contrast, human fMRI studies reported haemodynamic and metabolic downregulation accompanying neuronal inhibition in motor39 and visual cortices40, suggesting that the sustained negative BOLD response (NBR) is a marker of neuronal deactivation. Similarly, combined fMRI and electrophysiological experiments showed a clear correspondence of NBR and decreased population spiking in haemodynamically ‘negative’ areas in the monkey primary visual cortex41. Decreases in blood oxygenation and volume were also found to be co-localized with predominant neuronal inhibition and arteriolar vasoconstriction during somatosensory stimulation in rats42. Thus, without understanding the intrinsic correlation between direct or indirect inhibitory activity and concomitant changes in energy metabolism in a given situation, conclusions cannot be drawn. Unfortunately, the few published theoretical estimates of energy budget have not considered the metabolic costs of spikes in interneurons and of the inhibitory postsynaptic potentials (IPSPs) they produce43. Modelling of inhibition is unlikely to be straightfor￾ward. On the one hand, the density of cortical inhibitory neurons is 10–15 times lower than excitatory neurons16, and for each one of them the electrochemical gradient, down which Cl2 moves postsy￾naptically at inhibitory synapses, is weaker than that of Na1 at excit￾atory synapses, requiring less energy to pump Cl2 back. In fact, the transport cycles of the cation–chloride co-transporters, which have a key role in intracellular Cl2 regulation, are driven without the direct hydrolysis of ATP, by using the energy from the cation gradients generated by the Na,K-ATPase44. On the other hand, inhibitory inter￾neurons are fast spiking45,46. For example, the firing of pyramidal cells in hippocampus is 1.4 Hz, whereas that of interneurons in the strata pyramidale and oriens is 15 Hz and 10 Hz, respectively. Similarly, cortical inhibitory interneurons may discharge 2–3 times faster than pyramidal cells47. In principle, inhibition may increase or decrease energy consumption depending on the contribution of the afore￾mentioned factors (for a recent comprehensive review on inhibitory neurons and brain metabolism, see ref. 48). Last but not least, neu￾rons directly affect microvessels. Pericytes, the flat, contractile con￾nective-tissue cells, often attached to the abluminal surface of the capillary endothelial cells, might directly alter CBF in response to changes in neural activity49. Moreover, a body of evidence suggests that increased activity of single inhibitory interneurons results in precise vasomotor responses in neighbouring brain microvessels, and these contractile or dilatory responses were attributed to arteriole smooth muscle50. The diversity of the haemodynamic responses to neural inhibition obtained in different types of experiments is therefore hardly surpris￾ing: it is primarily due to the fact that regional inhibition itself might have a number of different causes, including early shunting of the weak cortical input, leading to a reduction of recurrent excitation rather than an increase in summed inhibition; increased synaptic inhibition; shunting of the cortical output through the axo-axonic connections of the chandelier cells; or any combination thereof. In the first case inhibition might result in a clear NBR; in the other two it might reflect the local metabolism increases induced by the un￾affected input and its ongoing processing, resulting in fMRI activa￾tions. The fMRI responses might further blur the origin of inhibition owing to the direct effects of the latter on the arterioles and micro￾vessels. Evidently much research is needed to characterize the actual state of an area and its participation in behaviour, but quite independent of this fact, the nature of the EIN suggests that mass action and its surrogate haemodynamics are ambiguous signals, the interpretation of which must be constrained by the concurrent use of other meth￾odologies. Neurophysiological correlates of the BOLD signal EIN and mesoscopic neural signals. The active regions of the mem￾brane of a discharging neuron at any given time are considered to act as a current sink, whereas the inactive ones act as a current source for the active regions (see ‘Neural signals’ in Supplementary Information). The linear superposition of currents from all sinks and sources forms the extracellular field potential measured by microelectrodes. The extracellular field potential captures at least three different types of EIN activity: single-unit activity representing the action potentials of well isolated neurons next to the electrode tip, multiple unit activity reflecting the spiking of small neural popula￾tions in a sphere of 100–300 mm radius, and perisynaptic activity of a neural population within 0.5–3 mm of the electrode tip, which is reflected in the variation of the low-frequency components of the extracellular field potential. Multiple unit activity and local field potentials (LFPs) can be reliably segregated by frequency band sepa￾ration. A high-pass filter cutoff in the range of 500–1,000 Hz is used in most recordings to obtain the multiple unit activity, and a low-pass filter cutoff of approximately 250 Hz to obtain LFP. A large number of experiments have presented data indicating that such a band sepa￾ration does indeed underlie different neural events (see ‘Neural sig￾nals’ in Supplementary Information). LFP signals and their different band-limited components (alpha, beta, gamma, and so on) are invaluable for understanding cortical processing, as they are the only signs of integrative EIN processes. In fact, LFPs do not, as initially thought, solely reflect population post￾synaptic potentials, but also integrative soma–dendritic processes— including voltage-dependent membrane oscillations and after￾potentials following soma–dendritic spikes—that all together repres￾ent the local (perisynaptic) activity in a region (see ‘Neural signals’ in Supplementary Information). A shortcoming of the LFP is its ambi￾guity. A change in the power of LFP in a particular frequency band most likely occurs for any mode of operations of the EIN. As most of the excitatory input into an area is local, LFPs will also indirectly reflect some of the postsynaptic effects of pyramidal cell activity. In addition, LFPs have a certain neural-class bias, which in this case is determined by geometry and regional architecture. The arrangement of the pyramidal and Purkinje cells will give rise to large LFP mod￾ulations; in contrast, interneurons will contribute only weakly because of their star-shaped dendrites and their geometrical disorder. Finally, inhibitory synapses may occasionally act as ‘shunts’ for the excitatory currents through low-resistance channels, in which case large synaptic conductance changes may produce little effect in the membrane potential, and result in weak and hard-to-measure mul￾tiple unit activity and LFPs. When individual LFP bands are examined separately, local spiking activity is occasionally found to affect certain frequency bands, whereas that of neuromodulation affects others51–53. It is evident that the most useful information will not be derived by one type of signal alone, but rather by the study of relative changes in one signal or the other. Electrophysiological studies examining the individual contri￾butions of different LFP frequency bands, multiple unit activity, and spiking of individual neurons are probably our only realistic chance of gaining insights into the neural mechanisms of haemodynamic responses and their meaning in the context of different cognitive tasks. Mesoscopic signals and the BOLD signal. The relationship of neo￾cortical LFPs and spiking activity to the BOLD signal itself was exam￾ined directly in concurrent electrophysiology and fMRI experiments in the visual system of anaesthetized54 and alert55 monkeys. These studies found that the BOLD responses reflect input and intracortical processing rather than pyramidal cell output activity. Initially, both LFPs and spiking seemed to be correlated with the BOLD response, although quantitative analysis indicated that LFPs are better predic￾tors of the BOLD response than multiple-unit or single-unit spiking. The decisive finding leading to the papers’ conclusion, however, was not the degree of correlation between the neural and the fMRI responses or the differential contribution of any type of signal into the BOLD responses55, but rather the striking, undiminished haemo￾dynamic responses in cases where spiking was entirely absent des￾pite a clear and strong stimulus-induced modulation of the field REVIEWS NATUREjVol 453j12 June 2008 874 ©2008 Macmillan Publishers Limited. All rights reserved