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Oscillatory mechanisms of feedforward and feedback visual processing Ole Jensen1,2, Mathilde Bonnefond1, Tom R. Marshall1, and Paul Tiesinga1 1
Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, The Netherlands Swammerdam Institute for Life Sciences - Center for Neuroscience, University of Amsterdam, Science Park 904, Amsterdam, XH 1098 The Netherlands
2
Two recent monkey studies demonstrate that feedforward processing in the visual system is reflected by activity in the 40–90 Hz gamma band, whereas feedback is reflected by activity in the 5–18 Hz alpha and beta band. These findings can be applied to interpret human electrophysiological activity in complex visual tasks. The visual system has a clear hierarchical organization: simple features are represented in early visual regions and more complex features are represented in downstream areas. This convergence in the visual hierarchy introduces an information processing bottleneck when we operate in natural environments. This bottleneck is reduced by routing mechanisms that selectively gate and prioritize relevant information. Indeed, it has been demonstrated in many studies that processing in early visual regions is modulated by feedback that can serve to boost the impact of important representations, and furthermore that this feedback might be mediated by changes in long-distance neuronal synchronization [1]. In order to serve this routing function, feedback mechanisms must obey two constraints: firstly, they must rely on changes in dynamics that alter the response properties of sensory neurons in a split second. Secondly, feedforward and feedback processing must depend on different channels to avoid interference. Two recently published studies provide exciting and novel insight into this issue. A study by Bastos et al. applied electrocorticography (ECoG) grid implants in monkeys, thus allowing the characterization of oscillatory dynamics at eight levels in the visual hierarchy [2]. They employed a task in which the monkeys had to covertly attend to one of two stimuli (simple grating patterns). Task-modulated Granger causality was used to quantify the directional connectivity between recorded regions. The core finding was that the feedforward drive between the different levels in the hierarchy was associated with inter-regional phase-synchronization of the local field potential (LFP) in the gamma band. The feedback drive on the other hand was associated with phase-synchronization in the 14–18 Hz beta band. Furthermore, results from an earlier anatomical study [3] were used to determine for each connection whether it constituted an anatomical feedforward or feedbackward connection. The Corresponding author: Jensen, O. ([email protected]). 0166-2236/ ß 2015 Published by Elsevier Ltd. http://dx.doi.org/10.1016/j.tins.2015.02.006
functional hierarchy derived from the interregional interactions in the alpha and gamma band was flexible and changed according to behavioral context under the constraints provided by the anatomical hierarchy. In the second report, van Kerkoerle et al. [4] found related results studying intracranial laminar recordings in monkeys engaged in a figure-ground segregation task. In this task, the ‘figure’ is a texture that is superimposed on background texture (Figure 1). When the orientation of the figure-texture is orthogonal to the background, it is perceived as a different object. The team recorded both from V1 and its downstream target area V4. A Granger causality analysis revealed that V1 was driving V4 in the gamma band when the figure was in the receptive field of the recorded V1 neurons. When the figure was not in the receptive field, V4 was driving V1 in the 5–15 Hz alpha band. These findings were supported by microstimulation: a burst of electrical stimulation in V1 increased gamma power in V4. Conversely a burst of stimulation in V4 increased alpha band power in V1. Laminar recordings in V1 revealed that these frequency specific effects were associated with activity initiated in different cortical layers. Within a column, gamma-band activity was initiated in the granular layers after which it propagated to the superficial and deeper layers. Conversely, alphaband activity was initiated in superficial and deeper layers and then propagated towards the granular layers. These findings are consistent with the anatomical findings that feedback projections arrive in superficial and deep layers, whereas feedforward projections arrive in granular layers. While the study of van Kerkoerle et al. reported feedback effects in the 5–15 Hz band, Bastos et al. reported similar effects in the 14–18 Hz band. It remains unknown whether this discrepancy in frequency bands represents a difference in mechanisms or whether they reflect differences between animals or recording techniques. The beta activity in the Bastos et al. study was recorded from the brain surface using ECoG whereas the laminar recordings applied by van Kerkoerle allowed for resolving activity in different cortical layers (see Box 1). Nevertheless, the convergent findings from the two studies are highly interesting since they point to a general mechanism for implementing feedforward and feedback processing between different regions in the visual hierarchy. What mechanisms can support the routing of feedforward and feedback information? There are well-defined ideas for how synchronization in the gamma band can Trends in Neurosciences xx (2015) 1–3
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Figure 1. The control of feedforward and feedback processing in the visual system. The figure provides a putative wiring diagram for the frequency and layer specific feedforward and feedback processing consistent with the findings of van Kerkoerle et al. [4] and Bastos et al. [2]. (A) In the task applied by van Kerkoerle et al., figure-ground segregation occurs when the centrally presented figure has a different orientation than the background [4]. (B) The upper path is the case in which the V1 receptive field is in the ‘figure’ area. The lower path corresponds to the case when the ‘figure’ was outside the V1 receptive field. (C) Figure-ground segregation resulted in increased neuronal synchronization in the gamma band promoting a feedforward drive to V4 (thick green line) [2,4]. (D) As a consequence, the figure is amplified in the superficial layers of V4. The control condition was associated with a feedback drive from V4 to V1 in the alpha band (thick red line). As shown by van Kerkoerle et al., NMDA receptors communicated the feedback drive (associated with the red feedback lines). Given the relatively slow time-course of the NMDA receptors ðt 100 msÞ they will act as a lowpass filter. This property could serve to attenuate V1 gamma-band activity such that it is not fed back from V4 to V1 creating a feedback loop [15]; E). The alpha/beta band synchronization between V4 and V1 poses an interesting question: how is V4 selectively synchronized with V1 neurons representing the attended stimulus? In particular this synchronization needs to be selective in nature in order to appropriate route the feedback signal. This could be achieved by the thalamus. While this hypothesis was not tested by van Kerkoerle et al. and Bastos et al., it is in line with a recent study demonstrating that the pulvinar synchronizes higher level visual areas when spatial attention is allocated [9]. The thick blue lines indicate that the pulvinar selectively drives the alpha oscillations in the deeper layers of the deselected neocortical pathway.
support feedforward processing. Consider a set of neurons in area V1 anatomically connected to neurons in area V4 (Figure 1C). When neurons in V1 are synchronized within a 10–20 ms time-window, this allows for summing of Box 1. Alpha oscillation in monkeys. While there are thousands of publications on the alpha rhythm in humans, reports in monkeys are scarce. What might explain this discrepancy? One reason is that monkey research often focuses on quantifying single unit activity whereas cortical rhythms are a population phenomenon best detected in field potentials. Another reason is the finding that the alpha rhythm has generators in the deeper cortical layers [4,10,12–14]. Pyramidal cells in deep layer 5 have long dendrites arranged in parallel extending through the layers. This spatial arrangement of dendrites is required in order for the electrophysiological activity from a population of neurons to summate and generate a signal detectable by EEG and MEG. The dendritic currents of the layer 5 pyramidal cells are most likely a consequence of distal synaptic input and somatic hyperpolarizing membrane potentials (discussed in [10]). Therefore, EEG and MEG recordings are biased towards electrophysiological events associated with the deeper cortical layers. Monkey recordings are typically performed in granular and superficial layers where synchronization in the alpha band is less visible. Future animal research focusing on the activity in the deeper layers could thus help reconcile the findings in humans and animals on the relationship between the alpha and gamma rhythm. 2
synaptic input in V4. Synchronization in the gamma band provides the required timing and can serve as a mechanism for gain control [5]. Much less is known about how slow oscillations in the alpha and beta band implement top-down control. One proposal is that alpha oscillations serve to route information by inhibition of neuronal firing. The inhibition selectively disengages task-irrelevant pathways thereby allowing routing of information along the non-inhibited pathway [6,7]. It does however remain unknown how this is implemented physiologically. For instance, is the phasic inhibitory drive implemented via the activation of GABAergic neurons or is it a consequence of more complex columnar interactions between multiple subtypes of interneurons as explored by the model of Lee et al. [8]? It also remains unknown how the alpha oscillations are controlled in a top-down sense (Figure 1C). A recent study points to the involvement of the pulvinar [9]. Finally, we need to understand how the alpha/beta oscillations interact with the gamma band activity. While previous work has demonstrated alpha oscillations can decrease gamma power in a phasic manner [10], neither the van Kerkoerle et al. nor the Bastos et al. study reported on such interactions. Their findings are however consistent with the view that the alpha/beta activity could modulate gamma band activity.
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Spotlight One exciting aspect of the reported results is that they can be directly translated to the interpretation of human data. There are numerous findings in humans demonstrating that alpha band activity is strongly modulated by spatial attention and that it plays a direct role in the routing of information (reviewed in [6,7]). These modulations are strong even in the absence of visual input, demonstrating they are under top-down control. Gamma band activity modulated by attention is also often reported, for example, [11]. This gamma band activity is in particular strong during visual stimulation, suggesting that it is related to feedforward processing. The studies by van Kerkoerle et al. and Bastos et al. now provide novel insight into the laminar and anatomical organization of the oscillatory neuronal dynamics in visual processing, prompting interesting questions as to their neurophysiological basis. In particular, it would be of great value to understand how gamma and alpha oscillations interact in order to temporally organize neuronal coding in the visual system [7]. Further studies in animals and humans would help to undercover the interactions between oscillations in different frequency bands. Acknowledgments The authors gratefully acknowledge funding from EU FP7 grant 600925 and the NWO grants 635.100.023, 453.09.002, and 821.02.011.
References 1 von Stein, A. et al. (2000) Top-down processing mediated by interareal synchronization. Proc. Natl. Acad. Sci. U.S.A. 97, 14748–14753
Trends in Neurosciences xxx xxxx, Vol. xxx, No. x
2 Bastos, A.M. et al. (2015) Visual Areas Exert Feedforward and Feedback Influences through Distinct Frequency Channels. Neuron 85, 390–401 3 Markov, N.T. et al. (2014) Anatomy of hierarchy: feedforward and feedback pathways in macaque visual cortex. J. Comp. Neurol. 522, 225–259 4 van Kerkoerle, T. et al. (2014) Alpha and gamma oscillations characterize feedback and feedforward processing in monkey visual cortex. Proc. Natl. Acad. Sci. U.S.A. 111, 14332–14341 5 Tiesinga, P.H. et al. (2004) Synchronization as a mechanism for attentional gain modulation. Neurocomputing 58–60, 641–646 6 Klimesch, W. (2012) Alpha-band oscillations, attention, and controlled access to stored information. Trends Cogn. Sci. 16, 606–617 7 Jensen, O. et al. (2014) Temporal coding organized by coupled alpha and gamma oscillations prioritize visual processing. Trends Neurosci. 37, 357–369 8 Lee, J.H. et al. (2013) Top-down beta rhythms support selective attention via interlaminar interaction: a model. PLoS Comp. Biol. 9, e1003164 9 Saalmann, Y.B. et al. (2012) The pulvinar regulates information transmission between cortical areas based on attention demands. Science 337, 753–756 10 Spaak, E. et al. (2012) Layer-specific entrainment of gamma-band neural activity by the alpha rhythm in monkey visual cortex. Curr. Biol. 22, 2313–2318 11 Siegel, M. et al. (2008) Neuronal synchronization along the dorsal visual pathway reflects the focus of spatial attention. Neuron 60, 709–719 12 Lopes Da Silva, F.H. and Storm Van Leeuwen, W. (1977) The cortical source of the alpha rhythm. Neurosci. Lett. 6, 237–241 13 Buffalo, E.A. et al. (2011) Laminar differences in gamma and alpha coherence in the ventral stream. Proc. Natl. Acad. Sci. U.S.A. 108, 11262–11267 14 Bollimunta, A. et al. (2011) Neuronal mechanisms and attentional modulation of corticothalamic alpha oscillations. J. Neurosci. 31, 4935–4943 15 Tiesinga, P.H. (2012) Motifs in health and disease: the promise of circuit interrogation by optogenetics. Eur. J. Neurosci. 36, 2260–2272
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Spotlight
Oscillatory mechanisms of feedforward and feedback visual processing Ole Jensen1,2, Mathilde Bonnefond1, Tom R. Marshall1, and Paul Tiesinga1 1
Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, The Netherlands Swammerdam Institute for Life Sciences - Center for Neuroscience, University of Amsterdam, Science Park 904, Amsterdam, XH 1098 The Netherlands
2
Two recent monkey studies demonstrate that feedforward processing in the visual system is reflected by activity in the 40–90 Hz gamma band, whereas feedback is reflected by activity in the 5–18 Hz alpha and beta band. These findings can be applied to interpret human electrophysiological activity in complex visual tasks. The visual system has a clear hierarchical organization: simple features are represented in early visual regions and more complex features are represented in downstream areas. This convergence in the visual hierarchy introduces an information processing bottleneck when we operate in natural environments. This bottleneck is reduced by routing mechanisms that selectively gate and prioritize relevant information. Indeed, it has been demonstrated in many studies that processing in early visual regions is modulated by feedback that can serve to boost the impact of important representations, and furthermore that this feedback might be mediated by changes in long-distance neuronal synchronization [1]. In order to serve this routing function, feedback mechanisms must obey two constraints: firstly, they must rely on changes in dynamics that alter the response properties of sensory neurons in a split second. Secondly, feedforward and feedback processing must depend on different channels to avoid interference. Two recently published studies provide exciting and novel insight into this issue. A study by Bastos et al. applied electrocorticography (ECoG) grid implants in monkeys, thus allowing the characterization of oscillatory dynamics at eight levels in the visual hierarchy [2]. They employed a task in which the monkeys had to covertly attend to one of two stimuli (simple grating patterns). Task-modulated Granger causality was used to quantify the directional connectivity between recorded regions. The core finding was that the feedforward drive between the different levels in the hierarchy was associated with inter-regional phase-synchronization of the local field potential (LFP) in the gamma band. The feedback drive on the other hand was associated with phase-synchronization in the 14–18 Hz beta band. Furthermore, results from an earlier anatomical study [3] were used to determine for each connection whether it constituted an anatomical feedforward or feedbackward connection. The Corresponding author: Jensen, O. ([email protected]). 0166-2236/ ß 2015 Published by Elsevier Ltd. http://dx.doi.org/10.1016/j.tins.2015.02.006
functional hierarchy derived from the interregional interactions in the alpha and gamma band was flexible and changed according to behavioral context under the constraints provided by the anatomical hierarchy. In the second report, van Kerkoerle et al. [4] found related results studying intracranial laminar recordings in monkeys engaged in a figure-ground segregation task. In this task, the ‘figure’ is a texture that is superimposed on background texture (Figure 1). When the orientation of the figure-texture is orthogonal to the background, it is perceived as a different object. The team recorded both from V1 and its downstream target area V4. A Granger causality analysis revealed that V1 was driving V4 in the gamma band when the figure was in the receptive field of the recorded V1 neurons. When the figure was not in the receptive field, V4 was driving V1 in the 5–15 Hz alpha band. These findings were supported by microstimulation: a burst of electrical stimulation in V1 increased gamma power in V4. Conversely a burst of stimulation in V4 increased alpha band power in V1. Laminar recordings in V1 revealed that these frequency specific effects were associated with activity initiated in different cortical layers. Within a column, gamma-band activity was initiated in the granular layers after which it propagated to the superficial and deeper layers. Conversely, alphaband activity was initiated in superficial and deeper layers and then propagated towards the granular layers. These findings are consistent with the anatomical findings that feedback projections arrive in superficial and deep layers, whereas feedforward projections arrive in granular layers. While the study of van Kerkoerle et al. reported feedback effects in the 5–15 Hz band, Bastos et al. reported similar effects in the 14–18 Hz band. It remains unknown whether this discrepancy in frequency bands represents a difference in mechanisms or whether they reflect differences between animals or recording techniques. The beta activity in the Bastos et al. study was recorded from the brain surface using ECoG whereas the laminar recordings applied by van Kerkoerle allowed for resolving activity in different cortical layers (see Box 1). Nevertheless, the convergent findings from the two studies are highly interesting since they point to a general mechanism for implementing feedforward and feedback processing between different regions in the visual hierarchy. What mechanisms can support the routing of feedforward and feedback information? There are well-defined ideas for how synchronization in the gamma band can Trends in Neurosciences xx (2015) 1–3
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Figure 1. The control of feedforward and feedback processing in the visual system. The figure provides a putative wiring diagram for the frequency and layer specific feedforward and feedback processing consistent with the findings of van Kerkoerle et al. [4] and Bastos et al. [2]. (A) In the task applied by van Kerkoerle et al., figure-ground segregation occurs when the centrally presented figure has a different orientation than the background [4]. (B) The upper path is the case in which the V1 receptive field is in the ‘figure’ area. The lower path corresponds to the case when the ‘figure’ was outside the V1 receptive field. (C) Figure-ground segregation resulted in increased neuronal synchronization in the gamma band promoting a feedforward drive to V4 (thick green line) [2,4]. (D) As a consequence, the figure is amplified in the superficial layers of V4. The control condition was associated with a feedback drive from V4 to V1 in the alpha band (thick red line). As shown by van Kerkoerle et al., NMDA receptors communicated the feedback drive (associated with the red feedback lines). Given the relatively slow time-course of the NMDA receptors ðt 100 msÞ they will act as a lowpass filter. This property could serve to attenuate V1 gamma-band activity such that it is not fed back from V4 to V1 creating a feedback loop [15]; E). The alpha/beta band synchronization between V4 and V1 poses an interesting question: how is V4 selectively synchronized with V1 neurons representing the attended stimulus? In particular this synchronization needs to be selective in nature in order to appropriate route the feedback signal. This could be achieved by the thalamus. While this hypothesis was not tested by van Kerkoerle et al. and Bastos et al., it is in line with a recent study demonstrating that the pulvinar synchronizes higher level visual areas when spatial attention is allocated [9]. The thick blue lines indicate that the pulvinar selectively drives the alpha oscillations in the deeper layers of the deselected neocortical pathway.
support feedforward processing. Consider a set of neurons in area V1 anatomically connected to neurons in area V4 (Figure 1C). When neurons in V1 are synchronized within a 10–20 ms time-window, this allows for summing of Box 1. Alpha oscillation in monkeys. While there are thousands of publications on the alpha rhythm in humans, reports in monkeys are scarce. What might explain this discrepancy? One reason is that monkey research often focuses on quantifying single unit activity whereas cortical rhythms are a population phenomenon best detected in field potentials. Another reason is the finding that the alpha rhythm has generators in the deeper cortical layers [4,10,12–14]. Pyramidal cells in deep layer 5 have long dendrites arranged in parallel extending through the layers. This spatial arrangement of dendrites is required in order for the electrophysiological activity from a population of neurons to summate and generate a signal detectable by EEG and MEG. The dendritic currents of the layer 5 pyramidal cells are most likely a consequence of distal synaptic input and somatic hyperpolarizing membrane potentials (discussed in [10]). Therefore, EEG and MEG recordings are biased towards electrophysiological events associated with the deeper cortical layers. Monkey recordings are typically performed in granular and superficial layers where synchronization in the alpha band is less visible. Future animal research focusing on the activity in the deeper layers could thus help reconcile the findings in humans and animals on the relationship between the alpha and gamma rhythm. 2
synaptic input in V4. Synchronization in the gamma band provides the required timing and can serve as a mechanism for gain control [5]. Much less is known about how slow oscillations in the alpha and beta band implement top-down control. One proposal is that alpha oscillations serve to route information by inhibition of neuronal firing. The inhibition selectively disengages task-irrelevant pathways thereby allowing routing of information along the non-inhibited pathway [6,7]. It does however remain unknown how this is implemented physiologically. For instance, is the phasic inhibitory drive implemented via the activation of GABAergic neurons or is it a consequence of more complex columnar interactions between multiple subtypes of interneurons as explored by the model of Lee et al. [8]? It also remains unknown how the alpha oscillations are controlled in a top-down sense (Figure 1C). A recent study points to the involvement of the pulvinar [9]. Finally, we need to understand how the alpha/beta oscillations interact with the gamma band activity. While previous work has demonstrated alpha oscillations can decrease gamma power in a phasic manner [10], neither the van Kerkoerle et al. nor the Bastos et al. study reported on such interactions. Their findings are however consistent with the view that the alpha/beta activity could modulate gamma band activity.
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Spotlight One exciting aspect of the reported results is that they can be directly translated to the interpretation of human data. There are numerous findings in humans demonstrating that alpha band activity is strongly modulated by spatial attention and that it plays a direct role in the routing of information (reviewed in [6,7]). These modulations are strong even in the absence of visual input, demonstrating they are under top-down control. Gamma band activity modulated by attention is also often reported, for example, [11]. This gamma band activity is in particular strong during visual stimulation, suggesting that it is related to feedforward processing. The studies by van Kerkoerle et al. and Bastos et al. now provide novel insight into the laminar and anatomical organization of the oscillatory neuronal dynamics in visual processing, prompting interesting questions as to their neurophysiological basis. In particular, it would be of great value to understand how gamma and alpha oscillations interact in order to temporally organize neuronal coding in the visual system [7]. Further studies in animals and humans would help to undercover the interactions between oscillations in different frequency bands. Acknowledgments The authors gratefully acknowledge funding from EU FP7 grant 600925 and the NWO grants 635.100.023, 453.09.002, and 821.02.011.
References 1 von Stein, A. et al. (2000) Top-down processing mediated by interareal synchronization. Proc. Natl. Acad. Sci. U.S.A. 97, 14748–14753
Trends in Neurosciences xxx xxxx, Vol. xxx, No. x
2 Bastos, A.M. et al. (2015) Visual Areas Exert Feedforward and Feedback Influences through Distinct Frequency Channels. Neuron 85, 390–401 3 Markov, N.T. et al. (2014) Anatomy of hierarchy: feedforward and feedback pathways in macaque visual cortex. J. Comp. Neurol. 522, 225–259 4 van Kerkoerle, T. et al. (2014) Alpha and gamma oscillations characterize feedback and feedforward processing in monkey visual cortex. Proc. Natl. Acad. Sci. U.S.A. 111, 14332–14341 5 Tiesinga, P.H. et al. (2004) Synchronization as a mechanism for attentional gain modulation. Neurocomputing 58–60, 641–646 6 Klimesch, W. (2012) Alpha-band oscillations, attention, and controlled access to stored information. Trends Cogn. Sci. 16, 606–617 7 Jensen, O. et al. (2014) Temporal coding organized by coupled alpha and gamma oscillations prioritize visual processing. Trends Neurosci. 37, 357–369 8 Lee, J.H. et al. (2013) Top-down beta rhythms support selective attention via interlaminar interaction: a model. PLoS Comp. Biol. 9, e1003164 9 Saalmann, Y.B. et al. (2012) The pulvinar regulates information transmission between cortical areas based on attention demands. Science 337, 753–756 10 Spaak, E. et al. (2012) Layer-specific entrainment of gamma-band neural activity by the alpha rhythm in monkey visual cortex. Curr. Biol. 22, 2313–2318 11 Siegel, M. et al. (2008) Neuronal synchronization along the dorsal visual pathway reflects the focus of spatial attention. Neuron 60, 709–719 12 Lopes Da Silva, F.H. and Storm Van Leeuwen, W. (1977) The cortical source of the alpha rhythm. Neurosci. Lett. 6, 237–241 13 Buffalo, E.A. et al. (2011) Laminar differences in gamma and alpha coherence in the ventral stream. Proc. Natl. Acad. Sci. U.S.A. 108, 11262–11267 14 Bollimunta, A. et al. (2011) Neuronal mechanisms and attentional modulation of corticothalamic alpha oscillations. J. Neurosci. 31, 4935–4943 15 Tiesinga, P.H. (2012) Motifs in health and disease: the promise of circuit interrogation by optogenetics. Eur. J. Neurosci. 36, 2260–2272
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