between the purpose and its functional basis, and recognize that the activation pattern of motor cortex neurons does two things—it specifies for the peripheral motor system both what to do and how to do it. REFERENCES Ajemian, R., Green, A., Bullock, D., Sergio, L., Kalaska, J., and Grossberg, S. (2008). Neuron 58, this issue, 414–428. Crutcher, M.D., and Alexander, G.E. (1990). J. Neurophysiol. 64, 151–163. Evarts, E.V. (1968). J. Neurophysiol. 31, 14–27. Georgopoulos, A.P., Kalaska, J.F., Caminiti, R., and Massey, J.T. (1982). J. Neurosci. 11, 1527– 1537. Georgopoulos, A.P., Schwartz, A.B., and Kettner, R.E. (1986). Science 233, 1416–1419. Georgopoulos, A.P., Ashe, J., Smyrnis, N., and Taira, M. (1992). Science 256, 1692–1695. Hubel, D.H., and Wiesel, T.N. (1962). J. Physiol. 160, 106–154. Kalaska, J.F., Cohen, D.A., Hyde, M.L., and Prud’- homme, M. (1989). J. Neurosci. 6, 2080–2102. Lemon, R.N. (2008). Annu. Rev. Neurosci., in press. Published online April 4, 2008. 10.1146/annurev. neuro.31.060407.125547. Lennie, P., and Movshon, J.A. (2005). J. Opt. Soc. Am. A 22, 2013–2033. Moran, D.W., and Schwartz, A.B. (1999). J. Neuro- physiol. 82, 2676–2692. Pesaran, B., Nelson, M.J., and Andersen, R.A. (2006). Neuron 51, 125–134. Scott, S.H., and Kalaska, J.F. (1997). J. Neurophy- siol. 77, 826–852. Sergio, L.E., and Kalaska, J.F. (2003). J. Neurophy- siol. 89, 212–228. Sergio, L.E., Hamel-Pa ˆ quet, C., and Kalaska, J.F. (2005). J. Neurophysiol. 94, 2353–2378. Finding Gamma Pascal Fries, 1,2, * Rene ´ Scheeringa, 1 and Robert Oostenveld 1 1 F.C. Donders Centre for Cognitive Neuroimaging, Radboud University Nijmegen, 6525 EN Nijmegen, The Netherlands 2 Department of Biophysics, Donders Centre for Neuroscience, Radboud University Nijmegen, 6525 EZ Nijmegen, The Netherlands *Correspondence: pascal.fries@fcdonders.ru.nl DOI 10.1016/j.neuron.2008.04.020 Neuronal gamma-band synchronization is central for cognition. Respective studies in human subjects fo- cused on a visually induced transient enhancement of broadband EEG power. In this issue of Neuron, Yuval-Greenberg et al. demonstrate that this EEG response is an artifact of microsaccades, raising the ques- tion of whether gamma-band synchronization can be assessed with EEG. When networks of neurons are activated, they engage in synchronous rhythmic activity in the gamma-frequency range (30–100 Hz) (Gray et al., 1989). This gamma-band synchronization affects neuronal interactions (Womelsdorf et al., 2007) and thereby subserves several cen- tral cognitive functions, including percep- tual binding (Gray et al., 1989), attentional selection (Fries et al., 2001), and working memory maintenance (Pesaran et al., 2002). These functions of gamma-band synchronization have been revealed in numerous experiments in animals, using microelectrodes that record single neu- rons, small groups of neurons, or the local field potential (LFP, a sort of EEG re- corded inside the neuropil). The LFP is due to intra- and extracellular current flows that can also be measured noninva- sively as magnetoencephalogram (MEG) or electroencephalogram (EEG). The EEG has been used extensively in human cognitive neuroscience, because it is relatively cheap and easy, but nevertheless delivers noninvasive mea- surements of human brain activity with millisecond temporal precision. This pre- cision has been exploited predominantly to study brain responses with a strict tem- poral relation to either a sensory stimulus, a motor response, or any other externally accessible event. The respective event is used to trigger the averaging of EEG epochs to obtain the event-related poten- tial (ERP). The underlying rationale is that any brain response related to the event is phase locked to it and survives averag- ing, while anything else is noise and is re- moved through the averaging. However, the absence of phase locking is precisely a characteristic feature of the neuronal gamma-band synchronization that had been observed in animals. The microelec- trode recordings in animals revealed consistently that, for example, visual stim- uli induced synchronized rhythms that oc- curred in each trial with a different phase relation to stimulus onset. The variable phase relation makes those components disappear in ERPs, and they can only be revealed if the spectral (frequency-wise) power of neuronal activity is estimated separately per trial and only then aver- aged. Such a power analysis in turn retains not only the interesting gamma-band rhythm, but also power from, for example, small muscle artifacts. These muscle artifacts contain power actually predomi- nantly in the gamma band, and it is precisely this reason why most re- searchers prefer to low-pass filter EEG signals around 30 Hz, eliminating many potential artifacts but also any potential gamma-band activity. Thus, both the Neuron 58, May 8, 2008 ª2008 Elsevier Inc. 303 Neuron Previews