This review highlights work showing that spectrally distributed oscillations and their coupling have functional relevance for sensorimotor processing.
Palva, S., & Palva, J. M. (2018). Roles of brain criticality and multiscale oscillations in temporal predictions for sensorimotor processing. Trends in Neurosciences, 41(10), 729-743.
Low-frequency synchrony between the anterior cingulate and orbitofrontal cortex is diminished when errors are made.
Fatahi, Z., Haghparast, A., Khani, A., & Kermani, M. (2017). Functional connectivity between Anterior Cingulate cortex and Orbitofrontal cortex during value-based decision making. Neurobiology of Learning and Memory.
There is growing evidence that bottom-up sensory inputs are associated with gamma oscillations (30-120 Hz) while top-down control depends on lower frequencies from delta through beta (1-30 Hz). This review argues that phase-phase synchrony across different frequencies integrates, coordinates, and regulates the neural assemblies in different frequency bands.
Palva, J. M., & Palva, S. (2017). Functional integration across oscillation frequencies by cross‐frequency phase synchronization. European Journal of Neuroscience.
MEG study in humans shows the functional significance of high alpha-band synchrony for visual attention.
Lobier, M., Palva, J. M., & Palva, S. (2017). High-alpha band synchronization across frontal, parietal and visual cortex mediates behavioral and neuronal effects of visuospatial attention. bioRxiv, 165563.
A model showing how neural coherence can flexibly route information. If you have a better idea of what underlies cognitive flexibility, I’d like to hear it.
Flexible information routing by transient synchrony
Agostina Palmigiano, Theo Geisel, Fred Wolf & Demian Battaglia
This study shows the role of alpha and beta oscillations in the prefrontal cortex and frontal eye fields in a classic test of cognitive control: anti-saccades. It also shows how these oscillatory patterns develop with adulthood.
Hwang, Kai, et al. “Frontal preparatory neural oscillations associated with cognitive control: A developmental study comparing young adults and adolescents.” NeuroImage (2016).
I like to say that anatomy is the road-and-highway system, activity is the traffic, and oscillations are the traffic lights. So, here you go:
Human brain networks function in connectome-specific harmonic waves.
Selen Atasoy, Isaac Donnelly & Joel Pearson
Nature Communications 7, Article number: 10340 doi:10.1038/ncomms10340
Pascal Fries and crew add to the mounting evidence that slow vs fast oscillations subserve feedback vs feedforward information flow in the cortex.
Michalareas, G., Vezoli, J., van Pelt, S., Schoffelen, J. M., Kennedy, H., & Fries, P. (2016). Alpha-Beta and Gamma Rhythms Subserve Feedback and Feedforward Influences among Human Visual Cortical Areas. Neuron.
Excellent review of how wide-spread brain areas use synchronized rhythms form networks for focusing attention. Very comprehensive and thorough on both a maco and micro-circuit level.
Pascal Fries walks us through the latest in the communication through coherence theory.
Review: Kei Igarashi argues that learning-related changes in synchrony between oscillatory activity in the cortex and hippocampus enhances neural communication and thus supports memory storage and recall.
Fries and colleagues report that coupling between theta and gamma rhythms support attention. The 4 Hz phase of gamma oscillations predicted the accuracy of the subject’s ability to detect stimulus dimming.
Landau, Ayelet Nina, et al. “Distributed Attention Is Implemented through Theta-Rhythmic Gamma Modulation.” Current Biology (2015).
Voytek et al provide more evidence that oscillatory dynamics play a critical role in neural communication and cognitive control. As humans performed tasks that required greater abstraction, there was an increase in theta synchrony between anterior and posterior frontal cortex. This may allow more anterior frontal cortex is communicate the higher level goals to motor cortex.
Oscillatory dynamics coordinating human frontal networks in support of goal maintenance
Bradley Voytek, Andrew S Kayser, David Badre, David Fegen, Edward F Chang, Nathan E Crone, Josef Parvizi, Robert T Knight & Mark D’Esposito. Nature Neuroscience
Kozma et al report brief periods of de-synchronization followed by intense synchronization. They speculate that this may correspond to an “aha!” moment when things “fall into place”. Interesting.
Kozma, Robert, Jeffery Jonathan Davis, and Walter J. Freeman. “Synchronized minima in ECoG power at frequencies between beta-gamma oscillations disclose cortical singularities in cognition.” Journal of Neuroscience and Neuroengineering 1.1 (2012): 13-23.
Matt Wilson and colleagues describe how oscillatory cycles can be viewed as functional units, how different oscillation phases can represent distinct computations, and how all this can be organized across cycles. Phew!
The title says it all (almost). Voloh et al found increased theta-gamma cross-frequency coupling between the anterior cingulate and prefrontal cortex during covert shifts of attention.
Theta–gamma coordination between anterior cingulate and prefrontal cortex indexes correct attention shifts
Benjamin Voloh, Taufik A. Valiante, Stefan Everling, and Thilo Womelsdorf
PNAS 2015 ; published ahead of print June 22, 2015, doi:10.1073/pnas.1500438112
Working memory has long been thought to depend on sustained firing of cortical neurons. However, single neurons showing unbroken sustained activity is rare and average population activity is often only strong near the end of a memory delay. Mark Stokes presents the intriguing hypothesis for activity-silent working memory. He suggests that working memory depends on patterns of functional connectivity between neurons, not sustained activity.
Kundu et al recorded EEG from humans during a short-term memory task. They found fronto-parietal coherence in different frequencies were associated with different memory functions. Alpha coherence was associated with maintenance of the information in memory. By contrast, the top-down filtering of distractions was associated with beta coherence. This adds to mounting evidence that specific frequency bands are associated with specific types of cortical processing like, for example, beta and top-down control.
Ardid et al use spike shape and firing variability to identify different classes in the primate prefrontal cortex. They ID four classes of broad spiking neurons and three classes of narrow spiking (inhibitory) neurons. These cell classes show different strength of synchrony to local field potential oscillations at specific frequencies. The authors suggest this reflects canonical cortical circuits with different functions.
Georgia Gregoriou and colleagues review the role of oscillations in the focusing of attention. They suggest that different frequencies reflect the biophysical properties of different cell types and that synchrony allows selective routing of information through these cell populations.
Frequency-specific hippocampal-prefrontal interactions during associative learning
Brincat, S.L. and Miller, E.K. (2015) Nature Neuroscience, advanced online publication
Much of our knowledge of the world depends on learning associations (for example, face-name), for which the hippocampus (HPC) and prefrontal cortex (PFC) are critical. HPC-PFC interactions have rarely been studied in monkeys, whose cognitive and mnemonic abilities are akin to those of humans. We found functional differences and frequency-specific interactions between HPC and PFC of monkeys learning object pair associations, an animal model of human explicit memory. PFC spiking activity reflected learning in parallel with behavioral performance, whereas HPC neurons reflected feedback about whether trial-and-error guesses were correct or incorrect. Theta-band HPC-PFC synchrony was stronger after errors, was driven primarily by PFC to HPC directional influences and decreased with learning. In contrast, alpha/beta-band synchrony was stronger after correct trials, was driven more by HPC and increased with learning. Rapid object associative learning may occur in PFC, whereas HPC may guide neocortical plasticity by signaling success or failure via oscillatory synchrony in different frequency bands.
MIT News Office: Neurons hum at different frequencies to tell the brain which memories it should store.
New discovery from the Miller Lab
Anne Trafton | MIT News Office
February 23, 2015
Our brains generate a constant hum of activity: As neurons fire, they produce brain waves that oscillate at different frequencies. Long thought to be merely a byproduct of neuron activity, recent studies suggest that these waves may play a critical role in communication between different parts of the brain.
A new study from MIT neuroscientists adds to that evidence. The researchers found that two brain regions that are key to learning — the hippocampus and the prefrontal cortex — use two different brain-wave frequencies to communicate as the brain learns to associate unrelated objects. Whenever the brain correctly links the objects, the waves oscillate at a higher frequency, called “beta,” and when the guess is incorrect, the waves oscillate at a lower “theta” frequency. Read more
Sacchet et al find that synchronization between the prefrontal and somatosensory cortex may underlie the disengagement of attention. When a cue signaled that a forthcoming tactile stimulus should be ignored, there was first an increase in alpha (7-14 Hz) synchrony between representations of the unattended stimulus, followed by an increase in beta (15-29 Hz) synchrony. This study shows how frequency specific interactions between frontal cortex and sensory cortex may underlie the focusing of attention.
Bressler and Richter review evidence that top-down processing in the cortex depends on synchronization of oscillatory rhythms between brain areas. More specifically, they hypothesize that beta band (13-30 Hz) synchrony conveys information about behavioral context (task information) to neurons in sensory cortex.
Andre Bastos and colleagues review an update the communication-through-coherence (CTC) hypothesis. They propose that bi-directional cortical communication involves separate feedforward and feedback mechanisms that are separate both anatomically and spectrally.