Key Points
-
Goal-directed, sensory-guided behaviour relies on both feedforward and feedback interactions between brain regions.
-
Studies of sensorimotor decision-making and top-down attention show that these large-scale interactions are reflected by the phase coherence and amplitude correlation of oscillations between brain regions.
-
Phase coherence and amplitude correlation provide insights into the large-scale neuronal interactions underlying cognition.
-
The frequencies of large-scale coherent oscillations reflect the neuronal circuit mechanisms of the canonical computations underlying cognition.
-
The frequencies of large-scale coherent oscillations may constitute indices, or 'fingerprints', of these canonical computations.
-
'Spectral fingerprints' provide a level of description situated in between the 'processes' defined by cognitive psychology and the underlying neuronal circuit mechanisms. This level of description may help to identify commonalities and differences between cognitive processes.
Abstract
Cognition results from interactions among functionally specialized but widely distributed brain regions; however, neuroscience has so far largely focused on characterizing the function of individual brain regions and neurons therein. Here we discuss recent studies that have instead investigated the interactions between brain regions during cognitive processes by assessing correlations between neuronal oscillations in different regions of the primate cerebral cortex. These studies have opened a new window onto the large-scale circuit mechanisms underlying sensorimotor decision-making and top-down attention. We propose that frequency-specific neuronal correlations in large-scale cortical networks may be 'fingerprints' of canonical neuronal computations underlying cognitive processes.
This is a preview of subscription content, access via your institution
Access options
Subscribe to this journal
Receive 12 print issues and online access
$189.00 per year
only $15.75 per issue
Buy this article
- Purchase on SpringerLink
- Instant access to full article PDF
Prices may be subject to local taxes which are calculated during checkout
Similar content being viewed by others
References
Crick, F. & Koch, C. A framework for consciousness. Nature Neurosci. 6, 119–126 (2003).
Singer, W. & Gray, C. M. Visual feature integration and the temporal correlation hypothesis. Annu. Rev. Neurosci. 18, 555–586 (1995).
von der Malsburg, C. The correlation theory of brain function. in Internal Report 81-2 (Max-Planck-Institute for Biophysical Chemistry, 1981).
Eckhorn, R. et al. Coherent oscillations: a mechanism of feature linking in the visual cortex? Multiple electrode and correlation analyses in the cat. Biol. Cybern. 60, 121–130 (1988).
Engel, A. K., Kreiter, A. K., König, P. & Singer, W. Synchronization of oscillatory neuronal responses between striate and extrastriate visual cortical areas of the cat. Proc. Natl Acad. Sci. USA 88, 6048–6052 (1991).
Gray, C. M., König, P., Engel, A. K. & Singer, W. Oscillatory responses in cat visual cortex exhibit inter-columnar synchronization which reflects global stimulus properties. Nature 338, 334–337 (1989).
Engel, A. K., König, P. & Singer, W. Direct physiological evidence for scene segmentation by temporal coding. Proc. Natl Acad. Sci. USA 88, 9136–9140 (1991).
Kreiter, A. K. & Singer, W. Stimulus-dependent synchronization of neuronal responses in the visual cortex of the awake macaque monkey. J. Neurosci. 16, 2381–2396 (1996).
Castelo-Branco, M., Goebel, R., Neuenschwander, S. & Singer, W. Neural synchrony correlates with surface segregation rules. Nature 405, 685–689 (2000).
Lamme, V. A. & Spekreijse, H. Neuronal synchrony does not represent texture segregation. Nature 396, 362–366 (1998).
Palanca, B. J. & DeAngelis, G. C. Does neuronal synchrony underlie visual feature grouping? Neuron 46, 333–346 (2005).
Thiele, A. & Stoner, G. Neuronal synchrony does not correlate with motion coherence in cortical area MT. Nature 421, 366–370 (2003).
Varela, F., Lachaux, J. P., Rodriguez, E. & Martinerie, J. The brainweb: phase synchronization and large-scale integration. Nature Rev. Neurosci. 2, 229–239 (2001).
Engel, A. K., Fries, P. & Singer, W. Dynamic predictions: oscillations and synchrony in top-down processing. Nature Rev. Neurosci. 2, 704–716 (2001).
Salinas, E. & Sejnowski, T. J. Correlated neuronal activity and the flow of neural information. Nature Rev. Neurosci. 2, 539–550 (2001).
Driver, J. & Noesselt, T. Multisensory interplay reveals crossmodal influences on 'sensory-specific' brain regions, neural responses, and judgments. Neuron 57, 11–23 (2008).
Ghazanfar, A. A. & Schroeder, C. E. Is neocortex essentially multisensory? Trends Cogn. Sci. 10, 278–285 (2006).
Schroeder, C. E. & Foxe, J. Multisensory contributions to low-level, 'unisensory' processing. Curr. Opin. Neurobiol. 15, 454–458 (2005).
Senkowski, D., Schneider, T. R., Foxe, J. J. & Engel, A. K. Crossmodal binding through neural coherence: implications for multisensory processing. Trends Neurosci. 31, 401–409 (2008).
Buzsaki, G. & Draguhn, A. Neuronal oscillations in cortical networks. Science 304, 1926–1929 (2004).
Schroeder, C. E. & Lakatos, P. Low-frequency neuronal oscillations as instruments of sensory selection. Trends Neurosci. 32, 9–18 (2008).
Fries, P. Neuronal gamma-band synchronization as a fundamental process in cortical computation. Annu. Rev. Neurosci. 32, 209–224 (2009).
Jensen, O. & Mazaheri, A. Shaping functional architecture by oscillatory alpha activity: gating by inhibition. Front. Hum. Neurosci. 4, 186 (2010).
Wang, X. J. Neurophysiological and computational principles of cortical rhythms in cognition. Physiol. Rev. 90, 1195–1268 (2010).
Donner, T. H. & Siegel, M. A framework for local cortical oscillation patterns. Trends Cogn. Sci. 15, 191–199 (2011).
Friston, K. Beyond phrenology: what can neuroimaging tell us about distributed circuitry? Annu. Rev. Neurosci. 25, 221–250 (2002).
Fries, P. A mechanism for cognitive dynamics: neuronal communication through neuronal coherence. Trends Cogn. Sci. 9, 474–480 (2005).
Abeles, M. Role of the cortical neuron: integrator or coincidence detector? Isr. J. Med. Sci. 18, 83–92 (1982).
König, P., Engel, A. K. & Singer, W. Integrator or coincidence detector? The role of the cortical neuron revisited. Trends Neurosci. 19, 130–137 (1996).
Azouz, R. & Gray, C. M. Dynamic spike threshold reveals a mechanism for synaptic coincidence detection in cortical neurons in vivo. Proc. Natl Acad. Sci. USA 97, 8110–8115 (2000).
Alonso, J. M., Usrey, W. M. & Reid, R. C. Precisely correlated firing in cells of the lateral geniculate nucleus. Nature 383, 815–819 (1996).
Bruno, R. M. & Sakmann, B. Cortex is driven by weak but synchronously active thalamocortical synapses. Science 312, 1622–1627 (2006).
Salinas, E. & Sejnowski, T. J. Impact of correlated synaptic input on output firing rate and variability in simple neuronal models. J. Neurosci. 20, 6193–6209 (2000).
Womelsdorf, T. et al. Modulation of neuronal interactions through neuronal synchronization. Science 316, 1609–1612 (2007).
Haider, B. & McCormick, D. A. Rapid neocortical dynamics: cellular and network mechanisms. Neuron 62, 171–189 (2009).
Lakatos, P. et al. An oscillatory hierarchy controlling neuronal excitability and stimulus processing in the auditory cortex. J. Neurophysiol. 94, 1904–1911 (2005).
Bruns, A., Eckhorn, R., Jokeit, H. & Ebner, A. Amplitude envelope correlation detects coupling among incoherent brain signals. Neuroreport 11, 1509–1514 (2000).
Leopold, D. A., Murayama, Y. & Logothetis, N. K. Very slow activity fluctuations in monkey visual cortex: implications for functional brain imaging. Cereb. Cortex 13, 422–433 (2003).
Shmuel, A. & Leopold, D. A. Neuronal correlates of spontaneous fluctuations in fMRI signals in monkey visual cortex: implications for functional connectivity at rest. Hum. Brain Mapp. 29, 751–761 (2008).
Munk, M. H., Roelfsema, P. R., König, P., Engel, A. K. & Singer, W. Role of reticular activation in the modulation of intracortical synchronization. Science 272, 271–274 (1996).
de Lange, F. P., Jensen, O., Bauer, M. & Toni, I. Interactions between posterior gamma and frontal alpha/beta oscillations during imagined actions. Front. Hum. Neurosci. 2, 7 (2008).
Donner, T. H., Siegel, M., Fries, P. & Engel, A. K. Buildup of choice-predictive activity in human motor cortex during perceptual decision making. Curr. Biol. 19, 1581–1585 (2009). This human MEG study was the first to directly link sensory and motor processing stages during visual decision-making, strongly suggesting a temporal integration of sensory evidence into motor plans.
Mazaheri, A. et al. Functional disconnection of frontal cortex and visual cortex in attention-deficit/hyperactivity disorder. Biol. Psychiatry 67, 617–623 (2010). This human EEG study assessed amplitude correlation between local oscillatory signatures to show that reduced fronto–occipital interactions reflect attentional control deficits in children with ADHD.
Mazaheri, A., Nieuwenhuis, I. L., van Dijk, H. & Jensen, O. Prestimulus alpha and mu activity predicts failure to inhibit motor responses. Hum. Brain Mapp. 30, 1791–1800 (2009).
Glimcher, P. W. The neurobiology of visual-saccadic decision making. Annu. Rev. Neurosci. 26, 133–179 (2003).
Gold, J. I. & Shadlen, M. N. The neural basis of decision making. Annu. Rev. Neurosci. 30, 535–574 (2007).
Heekeren, H. R., Marrett, S. & Ungerleider, L. G. The neural systems that mediate human perceptual decision making. Nature Rev. Neurosci. 9, 467–479 (2008).
Romo, R. & Salinas, E. Flutter discrimination: neural codes, perception, memory and decision making. Nature Rev. Neurosci. 4, 203–218 (2003).
Schall, J. D. Neural basis of deciding, choosing and acting. Nature Rev. Neurosci. 2, 33–42 (2001).
Siegel, M., Engel, A. K. & Donner, T. H. Cortical network dynamics of perceptual decision-making in the human brain. Front. Hum. Neurosci. 5, 21 (2011).
Gold, J. I. & Shadlen, M. N. Neural computations that underlie decisions about sensory stimuli. Trends Cogn. Sci. 5, 10–16 (2001).
Horwitz, G. D., Batista, A. P. & Newsome, W. T. Representation of an abstract perceptual decision in macaque superior colliculus. J. Neurophysiol. 91, 2281–2296 (2004).
Kim, J. N. & Shadlen, M. N. Neural correlates of a decision in the dorsolateral prefrontal cortex of the macaque. Nature Neurosci. 2, 176–185 (1999).
Donner, T. H., Sagi, D., Bonneh, Y. S. & Heeger, D. J. Opposite neural signatures of motion-induced blindness in human dorsal and ventral visual cortex. J. Neurosci. 28, 10298–10310 (2008).
Nienborg, H. & Cumming, B. G. Decision-related activity in sensory neurons reflects more than a neuron's causal effect. Nature 459, 89–92 (2009).
Ress, D. & Heeger, D. J. Neuronal correlates of perception in early visual cortex. Nature Neurosci. 6, 414–420 (2003).
Corbetta, M. & Shulman, G. L. Control of goal-directed and stimulus-driven attention in the brain. Nature Rev. Neurosci. 3, 201–215 (2002).
Driver, J., Blankenburg, F., Bestmann, S., Vanduffel, W. & Ruff, C. C. Concurrent brain-stimulation and neuroimaging for studies of cognition. Trends Cogn. Sci. 13, 319–327 (2009).
Kastner, S. & Ungerleider, L. G. Mechanisms of visual attention in the human cortex. Annu. Rev. Neurosci. 23, 315–341 (2000).
Moore, T. & Armstrong, K. M. Selective gating of visual signals by microstimulation of frontal cortex. Nature 421, 370–373 (2003).
Serences, J. T. & Yantis, S. Selective visual attention and perceptual coherence. Trends Cogn. Sci. 10, 38–45 (2006).
Zanto, T. P., Rubens, M. T., Thangavel, A. & Gazzaley, A. Causal role of the prefrontal cortex in top-down modulation of visual processing and working memory. Nature Neurosci. 14, 656–661 (2011).
Bressler, S. L., Coppola, R. & Nakamura, R. Episodic multiregional cortical coherence at multiple frequencies during visual task performance. Nature 366, 153–156 (1993).
Roelfsema, P. R., Engel, A. K., König, P. & Singer, W. Visuomotor integration is associated with zero time-lag synchronization among cortical areas. Nature 385, 157–161 (1997).
Miller, E. K. & Cohen, J. D. An integrative theory of prefrontal cortex function. Annu. Rev. Neurosci. 24, 167–202 (2001).
Desimone, R. & Duncan, J. Neural mechanisms of selective visual attention. Annu. Rev. Neurosci. 18, 193–222 (1995).
Schroeder, C. E., Wilson, D. A., Radman, T., Scharfman, H. & Lakatos, P. Dynamics of active sensing and perceptual selection. Curr. Opin. Neurobiol. 20, 172–176 (2010).
Uchida, N., Kepecs, A. & Mainen, Z. F. Seeing at a glance, smelling in a whiff: rapid forms of perceptual decision making. Nature Rev. Neurosci. 7, 485–491 (2006).
Rizzolatti, G., Riggio, L., Dascola, I. & Umilta, C. Reorienting attention across the horizontal and vertical meridians: evidence in favor of a premotor theory of attention. Neuropsychologia 25, 31–40 (1987).
Moore, T., Armstrong, K. M. & Fallah, M. Visuomotor origins of covert spatial attention. Neuron 40, 671–683 (2003).
Siegel, M., Donner, T. H., Oostenveld, R., Fries, P. & Engel, A. K. High-frequency activity in human visual cortex is modulated by visual motion strength. Cereb. Cortex 17, 732–741 (2007).
Donner, T. H. et al. Population activity in the human dorsal pathway predicts the accuracy of visual motion detection. J. Neurophysiol. 98, 345–359 (2007).
Siegel, M., Donner, T. H., Oostenveld, R., Fries, P. & Engel, A. K. Neuronal synchronization along the dorsal visual pathway reflects the focus of spatial attention. Neuron 60, 709–719 (2008). This human MEG study was the first to demonstrate that visuospatial attention modulates long-range coherence between frontal, parietal and visual cortices in a spatially selective fashion.
Usher, M. & McClelland, J. L. The time course of perceptual choice: the leaky, competing accumulator model. Psychol. Rev. 108, 550–592 (2001).
Smith, P. L. & Ratcliff, R. Psychology and neurobiology of simple decisions. Trends Neurosci. 27, 161–168 (2004).
Aoki, F., Fetz, E. E., Shupe, L., Lettich, E. & Ojemann, G. A. Changes in power and coherence of brain activity in human sensorimotor cortex during performance of visuomotor tasks. Biosystems 63, 89–99 (2001).
Brovelli, A. et al. Beta oscillations in a large-scale sensorimotor cortical network: directional influences revealed by Granger causality. Proc. Natl Acad. Sci. USA 101, 9849–9854 (2004).
Murthy, V. N. & Fetz, E. E. Coherent 25- to 35-Hz oscillations in the sensorimotor cortex of awake behaving monkeys. Proc. Natl Acad. Sci. USA 89, 5670–5674 (1992).
Wang, X. J. Decision making in recurrent neuronal circuits. Neuron 60, 215–234 (2008).
Pfurtscheller, G. & Lopes da Silva, F. H. Event-related EEG/MEG synchronization and desynchronization: basic principles. Clin. Neurophysiol. 110, 1842–1857 (1999).
Haegens, S. et al. Beta oscillations in the monkey sensorimotor network reflect somatosensory decision making. Proc. Natl Acad. Sci. USA 108, 10708–10713 (2011). This monkey electrophysiology study demonstrated decision-related modulations of beta-band oscillations across several frontal areas during a vibro-tactile discrimination task.
Hernandez, A. et al. Decoding a perceptual decision process across cortex. Neuron 66, 300–314 (2010).
Pesaran, B., Nelson, M. J. & Andersen, R. A. Free choice activates a decision circuit between frontal and parietal cortex. Nature 453, 406–409 (2008). This monkey electrophysiology study was the first to link large-scale multi-area recordings to decision-making and reported enhanced frontoparietal beta-band coherence during free decisions as compared to instructed decisions.
Rizzolatti, G., Riggio, L. & Sheliga, B. M. in Attention and Performance (ed. Moscovitch, C. U. M.) 231–265 (MIT Press, Cambridge, Massachusetts, USA, 1994).
Gregoriou, G. G., Gotts, S. J., Zhou, H. & Desimone, R. High-frequency, long-range coupling between prefrontal and visual cortex during attention. Science 324, 1207–1210 (2009). This monkey electrophysiology study demonstrated spatially selective attentional modulation of coherence between frontal and visual cortices and characterized in detail the temporal dynamics and directionality of oscillatory interactions.
Gross, J. et al. Modulation of long-range neural synchrony reflects temporal limitations of visual attention in humans. Proc. Natl Acad. Sci. USA 101, 13050–13055 (2004). This human MEG study was the first to demonstrate that frontoparietal beta-band coherence predicts performance in a demanding visual detection task.
Hipp, J. F., Engel, A. K. & Siegel, M. Oscillatory synchronization in large-scale cortical networks predicts perception. Neuron 69, 387–396 (2011). This human EEG study identified a large-scale coherent beta-band network across frontoparietal and visual cortices by using a new analysis approach that allows for imaging interacting networks across a full pair-wise cortico–cortical space.
Saalmann, Y. B., Pigarev, I. N. & Vidyasagar, T. R. Neural mechanisms of visual attention: how top-down feedback highlights relevant locations. Science 316, 1612–1615 (2007).
Buschman, T. J. & Miller, E. K. Top-down versus bottom-up control of attention in the prefrontal and posterior parietal cortices. Science 315, 1860–1862 (2007). This monkey electrophysiology study was the first to directly compare bottom-up and top-down attention and demonstrated frontoparietal coherence in the gamma- and beta-band for bottom-up and top-down attention, respectively.
Lindsley, D. B. Psychological phenomena and the electroencephalogram. Electroencephalogr. Clin. Neurophysiol. 4, 443–456 (1952).
Nunn, C. M. & Osselton, J. W. The influence of the EEG alpha rhythm on the perception of visual stimuli. Psychophysiology 11, 294–303 (1974).
Busch, N. A., Dubois, J. & VanRullen, R. The phase of ongoing EEG oscillations predicts visual perception. J. Neurosci. 29, 7869–7876 (2009).
Mathewson, K. E., Gratton, G., Fabiani, M., Beck, D. M. & Ro, T. To see or not to see: prestimulus alpha phase predicts visual awareness. J. Neurosci. 29, 2725–2732 (2009).
Worden, M. S., Foxe, J. J., Wang, N. & Simpson, G. V. Anticipatory biasing of visuospatial attention indexed by retinotopically specific alpha-band electroencephalography increases over occipital cortex. J. Neurosci. 20, RC63 (2000).
Cohen, M. X., van Gaal, S., Ridderinkhof, K. R. & Lamme, V. A. Unconscious errors enhance prefrontal-occipital oscillatory synchrony. Front. Hum. Neurosci. 3, 54 (2009).
Siegel, M., Kording, K. P. & König, P. Integrating top-down and bottom-up sensory processing by somato-dendritic interactions. J. Comput. Neurosci. 8, 161–173 (2000).
von Stein, A., Chiang, C. & König, P. Top-down processing mediated by interareal synchronization. Proc. Natl Acad. Sci. USA 97, 14748–14753 (2000).
Buffalo, E. A., Fries, P., Landman, R., Buschman, T. J. & Desimone, R. Laminar differences in gamma and alpha coherence in the ventral stream. Proc. Natl Acad. Sci. USA 108, 11262–11267 (2011).
Jones, S. R. et al. Quantitative analysis and biophysically realistic neural modeling of the MEG mu rhythm: rhythmogenesis and modulation of sensory-evoked responses. J. Neurophysiol. 102, 3554–3572 (2009).
Roopun, A. K. et al. Cholinergic neuromodulation controls directed temporal communication in neocortex in vitro. Front. Neural Circuits 4, 8 (2010).
Kayser, C. & Logothetis, N. K. Directed interactions between auditory and superior temporal cortices and their role in sensory integration. Front. Integr Neurosci. 3, 7 (2009).
Maier, J. X., Chandrasekaran, C. & Ghazanfar, A. A. Integration of bimodal looming signals through neuronal coherence in the temporal lobe. Curr. Biol. 18, 963–968 (2008).
Engel, A. K. & Fries, P. Beta-band oscillations-signalling the status quo? Curr. Opin. Neurobiol. 20, 156–165 (2010).
Palva, J. M., Monto, S., Kulashekhar, S. & Palva, S. Neuronal synchrony reveals working memory networks and predicts individual memory capacity. Proc. Natl Acad. Sci. USA 107, 7580–7585 (2010).
Spitzer, B., Wacker, E. & Blankenburg, F. Oscillatory correlates of vibrotactile frequency processing in human working memory. J. Neurosci. 30, 4496–4502 (2010).
Spitzer, B. & Blankenburg, F. Stimulus-dependent EEG activity reflects internal updating of tactile working memory in humans. Proc. Natl Acad. Sci. USA 108, 8444–8449 (2011).
Palva, S., Kulashekhar, S., Hamalainen, M. & Palva, J. M. Localization of cortical phase and amplitude dynamics during visual working memory encoding and retention. J. Neurosci. 31, 5013–5025 (2011).
Tallon-Baudry, C., Mandon, S., Freiwald, W. A. & Kreiter, A. K. Oscillatory synchrony in the monkey temporal lobe correlates with performance in a visual short-term memory task. Cereb. Cortex 14, 713–720 (2004).
Siegel, M., Warden, M. R. & Miller, E. K. Phase-dependent neuronal coding of objects in short-term memory. Proc. Natl Acad. Sci. USA 106, 21341–21346 (2009).
Tallon-Baudry, C., Bertrand, O. & Fischer, C. Oscillatory synchrony between human extrastriate areas during visual short-term memory maintenance. J. Neurosci. 21, RC177 (2001).
Fell, J. & Axmacher, N. The role of phase synchronization in memory processes. Nature Rev. Neurosci. 12, 105–118 (2011).
Roopun, A. K. et al. Period concatenation underlies interactions between gamma and beta rhythms in neocortex. Front. Cell Neurosci. 2, 1 (2008).
Kopell, N., Whittington, M. A. & Kramer, M. A. Neuronal assembly dynamics in the beta1 frequency range permits short-term memory. Proc. Natl Acad. Sci. USA 108, 3779–3784 (2011).
VanRullen, R. & Koch, C. Is perception discrete or continuous? Trends Cogn. Sci. 7, 207–213 (2003).
Buschman, T. J. & Miller, E. K. Shifting the spotlight of attention: evidence for discrete computations in cognition. Front. Hum. Neurosci. 4, 194 (2010).
Luo, H. & Poeppel, D. Phase patterns of neuronal responses reliably discriminate speech in human auditory cortex. Neuron 54, 1001–1010 (2007).
Bosman, C. A., Womelsdorf, T., Desimone, R. & Fries, P. A microsaccadic rhythm modulates gamma-band synchronization and behavior. J. Neurosci. 29, 9471–9480 (2009).
Crochet, S. & Petersen, C. C. Correlating whisker behavior with membrane potential in barrel cortex of awake mice. Nature Neurosci. 9, 608–610 (2006).
Ganguly, K. & Kleinfeld, D. Goal-directed whisking increases phase-locking between vibrissa movement and electrical activity in primary sensory cortex in rat. Proc. Natl Acad. Sci. USA 101, 12348–12353 (2004).
Kay, L. M. et al. Olfactory oscillations: the what, how and what for. Trends Neurosci. 32, 207–214 (2009).
Lakatos, P., Karmos, G., Mehta, A. D., Ulbert, I. & Schroeder, C. E. Entrainment of neuronal oscillations as a mechanism of attentional selection. Science 320, 110–113 (2008).
Lakatos, P. et al. The leading sense: supramodal control of neurophysiological context by attention. Neuron 64, 419–430 (2009).
Buschman, T. J. & Miller, E. K. Serial, covert shifts of attention during visual search are reflected by the frontal eye fields and correlated with population oscillations. Neuron 63, 386–396 (2009).
Varela, F. J., Toro, A., John, E. R. & Schwartz, E. L. Perceptual framing and cortical alpha rhythm. Neuropsychologia 19, 675–686 (1981).
Busch, N. A. & VanRullen, R. Spontaneous EEG oscillations reveal periodic sampling of visual attention. Proc. Natl Acad. Sci. USA 107, 16048–16053 (2010).
Kopell, N., Ermentrout, G. B., Whittington, M. A. & Traub, R. D. Gamma rhythms and beta rhythms have different synchronization properties. Proc. Natl Acad. Sci. USA 97, 1867–1872 (2000).
von Stein, A. & Sarnthein, J. Different frequencies for different scales of cortical integration: from local gamma to long range alpha/theta synchronization. Int. J. Psychophysiol. 38, 301–313 (2000).
Miller, R. Theory of the normal waking EEG: from single neurones to waveforms in the alpha, beta and gamma frequency ranges. Int. J. Psychophysiol. 64, 18–23 (2007).
Ghazanfar, A. A., Chandrasekaran, C. & Logothetis, N. K. Interactions between the superior temporal sulcus and auditory cortex mediate dynamic face/voice integration in rhesus monkeys. J. Neurosci. 28, 4457–4469 (2008).
Felleman, D. J. & Van Essen, D. C. Distributed hierarchical processing in the primate cerebral cortex. Cereb. Cortex 1, 1–47 (1991).
Barone, P., Batardiere, A., Knoblauch, K. & Kennedy, H. Laminar distribution of neurons in extrastriate areas projecting to visual areas V1 and V4 correlates with the hierarchical rank and indicates the operation of a distance rule. J. Neurosci. 20, 3263–3281 (2000).
van Kerkoerle, T. J., Self, M., Poort, J., van der Togt, C. & Roelfsema, P. R. High frequencies flow in the feed-forward direction through the different layers of monkey primary visual cortex while low frequencies flow in the recurrent direction. Soc. Neurosci. Abstr. 270.8 (Washington, DC, 12–16 Nov 2011).
Buhl, E. H., Tamas, G. & Fisahn, A. Cholinergic activation and tonic excitation induce persistent gamma oscillations in mouse somatosensory cortex in vitro. J. Physiol. 513, 117–126 (1998).
Maier, A., Adams, G. K., Aura, C. & Leopold, D. A. Distinct superficial and deep laminar domains of activity in the visual cortex during rest and stimulation. Front. Syst. Neurosci. 4, 31 (2010).
Roopun, A. K. et al. A beta2-frequency (20–30 Hz) oscillation in nonsynaptic networks of somatosensory cortex. Proc. Natl Acad. Sci. USA 103, 15646–15650 (2006).
Bollimunta, A., Chen, Y., Schroeder, C. E. & Ding, M. Neuronal mechanisms of cortical alpha oscillations in awake-behaving macaques. J. Neurosci. 28, 9976–9988 (2008).
Lopes Da Silva, F. H. & Storm Van Leeuwen, W. The cortical source of the alpha rhythm. Neurosci. Lett. 6, 237–241 (1977).
Silva, L. R., Amitai, Y. & Connors, B. W. Intrinsic oscillations of neocortex generated by layer 5 pyramidal neurons. Science 251, 432–435 (1991).
Sun, W. & Dan, Y. Layer-specific network oscillation and spatiotemporal receptive field in the visual cortex. Proc. Natl Acad. Sci. USA 106, 17986–17991 (2009).
Kramer, M. A. et al. Rhythm generation through period concatenation in rat somatosensory cortex. PLoS Comput. Biol. 4, e1000169 (2008).
Atallah, B. V. & Scanziani, M. Instantaneous modulation of gamma oscillation frequency by balancing excitation with inhibition. Neuron 62, 566–577 (2009).
Whittington, M. A., Traub, R. D., Kopell, N., Ermentrout, B. & Buhl, E. H. Inhibition-based rhythms: experimental and mathematical observations on network dynamics. Int. J. Psychophysiol. 38, 315–336 (2000).
Whittington, M. A., Stanford, I. M., Colling, S. B., Jefferys, J. G. & Traub, R. D. Spatiotemporal patterns of gamma frequency oscillations tetanically induced in the rat hippocampal slice. J. Physiol. 502, 591–607 (1997).
Bartos, M., Vida, I. & Jonas, P. Synaptic mechanisms of synchronized gamma oscillations in inhibitory interneuron networks. Nature Rev. Neurosci. 8, 45–56 (2007).
Cardin, J. A. et al. Driving fast-spiking cells induces gamma rhythm and controls sensory responses. Nature 459, 663–667 (2009).
Hasenstaub, A. et al. Inhibitory postsynaptic potentials carry synchronized frequency information in active cortical networks. Neuron 47, 423–435 (2005).
Sohal, V. S., Zhang, F., Yizhar, O. & Deisseroth, K. Parvalbumin neurons and gamma rhythms enhance cortical circuit performance. Nature 459, 698–702 (2009).
Heeger, D. J., Simoncelli, E. P. & Movshon, J. A. Computational models of cortical visual processing. Proc. Natl Acad. Sci. USA 93, 623–627 (1996).
Shapley, R., Hawken, M. & Ringach, D. L. Dynamics of orientation selectivity in the primary visual cortex and the importance of cortical inhibition. Neuron 38, 689–699 (2003).
Louie, K., Grattan, L. E. & Glimcher, P. W. Reward value-based gain control: divisive normalization in parietal cortex. J. Neurosci. 31, 10627–10639 (2011).
Reynolds, J. H. & Heeger, D. J. The normalization model of attention. Neuron 61, 168–185 (2009).
Zoccolan, D., Cox, D. D. & DiCarlo, J. J. Multiple object response normalization in monkey inferotemporal cortex. J. Neurosci. 25, 8150–8164 (2005).
Ohshiro, T., Angelaki, D. E. & DeAngelis, G. C. A normalization model of multisensory integration. Nature Neurosci. 14, 775–782 (2011).
Ray, S. & Maunsell, J. H. Differences in gamma frequencies across visual cortex restrict their possible use in computation. Neuron 67, 885–896 (2010).
Siegel, M. & König, P. A functional gamma-band defined by stimulus-dependent synchronization in area 18 of awake behaving cats. J. Neurosci. 23, 4251–4260 (2003).
Hyman, J. M., Zilli, E. A., Paley, A. M. & Hasselmo, M. E. Medial prefrontal cortex cells show dynamic modulation with the hippocampal theta rhythm dependent on behavior. Hippocampus 15, 739–749 (2005).
Jones, M. W. & Wilson, M. A. Theta rhythms coordinate hippocampal-prefrontal interactions in a spatial memory task. PLoS Biol. 3, e402 (2005).
Poch, C., Fuentemilla, L., Barnes, G. R. & Duzel, E. Hippocampal theta-phase modulation of replay correlates with configural-relational short-term memory performance. J. Neurosci. 31, 7038–7042 (2011).
Siapas, A. G., Lubenov, E. V. & Wilson, M. A. Prefrontal phase locking to hippocampal theta oscillations. Neuron 46, 141–151 (2005).
Sirota, A. et al. Entrainment of neocortical neurons and gamma oscillations by the hippocampal theta rhythm. Neuron 60, 683–697 (2008).
Buzsaki, G. Theta oscillations in the hippocampus. Neuron 33, 325–340 (2002).
Jensen, O. & Colgin, L. L. Cross-frequency coupling between neuronal oscillations. Trends Cogn. Sci. 11, 267–269 (2007).
Canolty, R. T. et al. High gamma power is phase-locked to theta oscillations in human neocortex. Science 313, 1626–1628 (2006).
Saleh, M., Reimer, J., Penn, R., Ojakangas, C. L. & Hatsopoulos, N. G. Fast and slow oscillations in human primary motor cortex predict oncoming behaviorally relevant cues. Neuron 65, 461–471 (2010).
Cohen, M. X., Elger, C. E. & Fell, J. Oscillatory activity and phase-amplitude coupling in the human medial frontal cortex during decision making. J. Cogn. Neurosci. 21, 390–402 (2009).
Voytek, B. et al. Shifts in gamma phase-amplitude coupling frequency from theta to alpha over posterior cortex during visual tasks. Front. Hum. Neurosci. 4, 191 (2010).
Handel, B. & Haarmeier, T. Cross-frequency coupling of brain oscillations indicates the success in visual motion discrimination. Neuroimage 45, 1040–1046 (2009).
Osipova, D., Hermes, D. & Jensen, O. Gamma power is phase-locked to posterior alpha activity. PLoS ONE 3, e3990 (2008).
Schack, B., Vath, N., Petsche, H., Geissler, H. G. & Moller, E. Phase-coupling of theta-gamma EEG rhythms during short-term memory processing. Int. J. Psychophysiol. 44, 143–163 (2002).
Demiralp, T. et al. Gamma amplitudes are coupled to theta phase in human EEG during visual perception. Int. J. Psychophysiol. 64, 24–30 (2007).
Mormann, F. et al. Phase/amplitude reset and theta-gamma interaction in the human medial temporal lobe during a continuous word recognition memory task. Hippocampus 15, 890–900 (2005).
American Psychiatric Association. Diagnostics and Statistical Manual of Mental Disorders 4th edn (American Psychiatric Press, Washington, DC, 2000).
Uhlhaas, P. J. & Singer, W. Abnormal neural oscillations and synchrony in schizophrenia. Nature Rev. Neurosci. 11, 100–113 (2010).
Lizio, R. et al. Electroencephalographic rhythms in Alzheimer's disease. Int. J. Alzheimers Dis. 2011, 927573 (2011).
Uhlhaas, P. J. & Singer, W. Neural synchrony in brain disorders: relevance for cognitive dysfunctions and pathophysiology. Neuron 52, 155–168 (2006).
Haenschel, C. et al. Cortical oscillatory activity is critical for working memory as revealed by deficits in early-onset schizophrenia. J. Neurosci. 29, 9481–9489 (2009).
Cho, R. Y., Konecky, R. O. & Carter, C. S. Impairments in frontal cortical gamma synchrony and cognitive control in schizophrenia. Proc. Natl Acad. Sci. USA 103, 19878–19883 (2006).
Spencer, K. M. et al. Abnormal neural synchrony in schizophrenia. J. Neurosci. 23, 7407–7411 (2003).
Lewis, D. A., Hashimoto, T. & Volk, D. W. Cortical inhibitory neurons and schizophrenia. Nature Rev. Neurosci. 6, 312–324 (2005).
Vierling-Claassen, D., Siekmeier, P., Stufflebeam, S. & Kopell, N. Modeling GABA alterations in schizophrenia: a link between impaired inhibition and altered gamma and beta range auditory entrainment. J. Neurophysiol. 99, 2656–2671 (2008).
Aston-Jones, G. & Cohen, J. D. An integrative theory of locus coeruleus-norepinephrine function: adaptive gain and optimal performance. Annu. Rev. Neurosci. 28, 403–450 (2005).
Goard, M. & Dan, Y. Basal forebrain activation enhances cortical coding of natural scenes. Nature Neurosci. 12, 1444–1449 (2009).
Yu, A. J. & Dayan, P. Uncertainty, neuromodulation, and attention. Neuron 46, 681–692 (2005).
Sara, S. J. The locus coeruleus and noradrenergic modulation of cognition. Nature Rev. Neurosci. 10, 211–223 (2009).
Rodriguez, R., Kallenbach, U., Singer, W. & Munk, M. H. Short- and long-term effects of cholinergic modulation on gamma oscillations and response synchronization in the visual cortex. J. Neurosci. 24, 10369–10378 (2004).
Saalmann, Y. B. & Kastner, S. Cognitive and perceptual functions of the visual thalamus. Neuron 71, 209–223 (2011).
Bollimunta, A., Mo, J., Schroeder, C. E. & Ding, M. Neuronal mechanisms and attentional modulation of corticothalamic alpha oscillations. J. Neurosci. 31, 4935–4943 (2011).
Lorincz, M. L., Kekesi, K. A., Juhasz, G., Crunelli, V. & Hughes, S. W. Temporal framing of thalamic relay-mode firing by phasic inhibition during the alpha rhythm. Neuron 63, 683–696 (2009).
Bekisz, M. & Wrobel, A. Coupling of beta and gamma activity in corticothalamic system of cats attending to visual stimuli. Neuroreport 10, 3589–3594 (1999).
Wrobel, A. Beta activity: a carrier for visual attention. Acta Neurobiol. Exp. (Wars) 60, 247–260 (2000).
Wrobel, A., Ghazaryan, A., Bekisz, M., Bogdan, W. & Kaminski, J. Two streams of attention-dependent beta activity in the striate recipient zone of cat's lateral posterior-pulvinar complex. J. Neurosci. 27, 2230–2240 (2007).
Jones, E. G. The thalamic matrix and thalamocortical synchrony. Trends Neurosci. 24, 595–601 (2001).
Lopes da Silva, F. H., Vos, J. E., Mooibroek, J. & Van Rotterdam, A. Relative contributions of intracortical and thalamo-cortical processes in the generation of alpha rhythms, revealed by partial coherence analysis. Electroencephalogr. Clin. Neurophysiol. 50, 449–456 (1980).
Shipp, S. The functional logic of cortico-pulvinar connections. Phil. Trans. R. Soc. Lond. B 358, 1605–1624 (2003).
Molotchnikoff, S. & Shumikhina, S. The lateral posterior-pulvinar complex modulation of stimulus-dependent oscillations in the cat visual cortex. Vision Res. 36, 2037–2046 (1996).
Shumikhina, S. & Molotchnikoff, S. Pulvinar participates in synchronizing neural assemblies in the visual cortex, in cats. Neurosci. Lett. 272, 135–139 (1999).
Vicente, R., Gollo, L. L., Mirasso, C. R., Fischer, I. & Pipa, G. Dynamical relaying can yield zero time lag neuronal synchrony despite long conduction delays. Proc. Natl Acad. Sci. USA 105, 17157–17162 (2008).
Theyel, B. B., Llano, D. A. & Sherman, S. M. The corticothalamocortical circuit drives higher-order cortex in the mouse. Nature Neurosci. 13, 84–88 (2010).
Nir, Y. et al. Coupling between neuronal firing rate, gamma LFP, and BOLD fMRI is related to interneuronal correlations. Curr. Biol. 17, 1275–1285 (2007).
Nir, Y. et al. Interhemispheric correlations of slow spontaneous neuronal fluctuations revealed in human sensory cortex. Nature Neurosci. 11, 1100–1108 (2008).
Fox, M. D. & Raichle, M. E. Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging. Nature Rev. Neurosci. 8, 700–711 (2007).
Haynes, J. D., Driver, J. & Rees, G. Visibility reflects dynamic changes of effective connectivity between V1 and fusiform cortex. Neuron 46, 811–821 (2005).
Haynes, J. D., Tregellas, J. & Rees, G. Attentional integration between anatomically distinct stimulus representations in early visual cortex. Proc. Natl Acad. Sci. USA 102, 14925–14930 (2005).
Freeman, J., Donner, T. H. & Heeger, D. J. Inter-area correlations in the ventral visual pathway reflect feature integration. J. Vis. 11 (4), 15 (2011).
Pantev, C. et al. Specific tonotopic organizations of different areas of the human auditory cortex revealed by simultaneous magnetic and electric recordings. Electroencephalogr. Clin. Neurophysiol. 94, 26–40 (1995).
Schoffelen, J. M. & Gross, J. Source connectivity analysis with MEG and EEG. Hum. Brain Mapp. 30, 1857–1865 (2009).
Nolte, G. et al. Identifying true brain interaction from EEG data using the imaginary part of coherency. Clin. Neurophysiol. 115, 2292–2307 (2004).
Blinn, K. A. Focal anterior temporal spikes from external rectus muscle. Electroencephalogr. Clin. Neurophysiol. 7, 299–302 (1955).
Yuval-Greenberg, S., Tomer, O., Keren, A. S., Nelken, I. & Deouell, L. Y. Transient induced gamma-band response in EEG as a manifestation of miniature saccades. Neuron 58, 429–441 (2008).
Keren, A. S., Yuval-Greenberg, S. & Deouell, L. Y. Saccadic spike potentials in gamma-band EEG: characterization, detection and suppression. NeuroImage 49, 2248–2263 (2010).
Reva, N. V. & Aftanas, L. I. The coincidence between late non-phase-locked gamma synchronization response and saccadic eye movements. Int. J. Psychophysiol. 51, 215–222 (2004).
Engbert, R. & Kliegl, R. Microsaccades uncover the orientation of covert attention. Vision Res. 43, 1035–1045 (2003).
Valsecchi, M., Betta, E. & Turatto, M. Visual oddballs induce prolonged microsaccadic inhibition. Exp. Brain Res. 177, 196–208 (2007).
Carl, C., Acik, A., König, P., Engel, A. K. & Hipp, J. F. The saccadic spike artifact in MEG. NeuroImage 59, 1657–1667 (2011).
Hughes, S. W. & Crunelli, V. Thalamic mechanisms of EEG alpha rhythms and their pathological implications. Neuroscientist 11, 357–372 (2005).
Lopes da Silva, F. H., van Lierop, T. H., Schrijer, C. F. & van Leeuwen, W. S. Organization of thalamic and cortical alpha rhythms: spectra and coherences. Electroencephalogr. Clin. Neurophysiol. 35, 627–639 (1973).
Acknowledgements
We thank J. F. Hipp and C. von Nicolai for helpful discussions and comments on the manuscript. This work was supported by grants from the European Union (HEALTH-F2-2008-200728, INFSO-ICT-270212 and ERC-2010-AdG-269716 to A.K.E.) and the German Research Foundation (GRK 1247/1/2 and SFB 936/1 to A.K.E).
Author information
Authors and Affiliations
Corresponding authors
Ethics declarations
Competing interests
The authors declare no competing financial interests.
Related links
Related links
FURTHER INFORMATION
Glossary
- Spectral analysis
-
A general term for analysis techniques (for example, Fourier transform or wavelet transform) that decompose time domain signals into their different frequency components.
- Multi-microelectrode recordings
-
Simultaneous recordings of single- or multi-unit activity from multiple electrodes implanted in the brain.
- Blood oxygen level-dependent functional MRI
-
(BOLD fMRI). Brain imaging technique that measures the haemodynamic response to neural activity based on changes in blood oxygenation.
- Sensor level
-
The level of the sensors, which record neuronal mass activity (for example, electroencephalography electrodes or magnetoencephalography sensors). Each sensor-level signal constitutes a linear mixture of the signals generated by many neuronal sources.
- Source reconstruction
-
Estimation of the sources of neuronal activity that underlie the electromagnetic signals measured at distant electroencephalography or magnetoencephalography sensors.
- Effective connectivity
-
The influence one neuronal system exerts on another; in many studies it is measured by quantifying Granger causality.
- 1/f spectrum
-
A spectrum for which the power P is inversely proportional to frequency f: P(f) ∝ 1/fa, a>0.
- Posterior parietal cortex
-
(PPC). An associative brain region that is centrally involved in spatial processing and controlling selective attention.
- Area MT
-
A region in the extrastriate visual cortex of the primate brain that is centrally involved in neuronal processing and perception of visual motion.
- Local field potentials
-
(LFPs). The low-frequency components of the extracellular voltage. The LFP mainly reflects average postsynaptic potentials surrounding the electrode tip.
- Frontal eye field
-
(FEF). A region in the frontal cortex that controls saccadic eye movements and the focus of visuospatial attention in the primate brain.
- Granger causality
-
A statistical measure that quantifies directed and potentially causal interactions between two simultaneous signals based on their mutual predictability.
- Attentional blink
-
The phenomenon that a second target is often missed when presented ∼200–500 ms after a first target in a rapid stream of visual stimuli.
- Go/no-go task
-
A task that requires a subject to perform a behavioural response (for example, button press) when one stimulus type appears, but to withhold a response when another stimulus type appears.
Rights and permissions
About this article
Cite this article
Siegel, M., Donner, T. & Engel, A. Spectral fingerprints of large-scale neuronal interactions. Nat Rev Neurosci 13, 121–134 (2012). https://doi.org/10.1038/nrn3137
Published:
Issue Date:
DOI: https://doi.org/10.1038/nrn3137
This article is cited by
-
A prefrontal-thalamic circuit encodes social information for social recognition
Nature Communications (2024)
-
Cognitive and Neuropathophysiological Outcomes of Gamma-tACS in Dementia: A Systematic Review
Neuropsychology Review (2024)
-
Dynamic brain functional states associated with inhibition control under different altitudes
Cognitive Neurodynamics (2024)
-
Frequency-specific functional difference between gyri and sulci in naturalistic paradigm fMRI
Brain Structure and Function (2024)
-
HMGB1 mediates synaptic loss and cognitive impairment in an animal model of sepsis-associated encephalopathy
Journal of Neuroinflammation (2023)