A mechanism for cognitive dynamics: neuronal communication through neuronal coherence

Fries, Pascal

doi:10.1016/j.tics.2005.08.011

Cited by 3,788 publications

(3,501 citation statements)

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“…6). The 'communication through coherence' hypothesis (Fries, 2005(Fries, , 2009 suggests that selective communication is achieved through coherence between firing rate oscillation in the sending region and oscillatory gain modulation in the receiving region, which allows a network to respond selectively to task-relevant target signals while ignoring irrelevant inputs. Computational modeling demonstrates that selective communication can indeed be achieved by coherent oscillatory gain modulation, but that the structure of oscillatory activity must satisfy certain constraints (Akam and Kullmann, 2012).…”

Section: Discussionmentioning

confidence: 99%

“…Introduction Synchronous brain rhythms represent a dynamic mechanism for coordinating neural activity across large-scale neuronal networks and controlling the timing of neuronal firing (Engel et al, 2001;Buzsaki and Draguhn, 2004;Wang, 2010). Evidence from the past two decades of research suggests that neural oscillations subserve important cognitive functions, including motor control (Fries, 2005;Schnitzler and Gross, 2005;Fetz, 2013). During sustained contractions, primary motor cortex shows oscillations in alpha (8 12 Hz) and beta (15 30 Hz) bands (Murthy and Fetz, 1992;Sanes and Donoghue, 1993;Baker et al, 2003).…”

Section: Introductionmentioning

confidence: 99%

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The reorganization of corticomuscular coherence during a transition between sensorimotor states

2014

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Recent research suggests that neural oscillations in di↵erent frequency bands support distinct and sometimes parallel processing streams in neural circuits. Studies of the neural dynamics of human motor control have primarily focused on oscillations in the beta band (15 30 Hz). During sustained muscle contractions, corticomuscular coherence is mainly present in the beta band, while coherence in the alpha (8 12 Hz) and gamma (30 80 Hz) bands has not been consistently found. Here we test the hypothesis that the frequency of corticomuscular coherence changes during transitions between sensorimotor states. Corticomuscular coherence was investigated in twelve participants making rapid transitions in force output between two targets. Corticomuscular coherence was present in the beta band during sustained contractions but vanished before movement onset, being replaced by transient synchronization in the alpha and gamma bands during dynamic force output. Analysis of the phase spectra suggested a time delay from muscle to cortex for alpha-band coherence, by contrast to a time delay from cortex to muscle for gamma-band coherence, indicating a↵erent and e↵erent corticospinal interactions respectively. Moreover, alpha and gamma -band coherence revealed distinct spatial topologies, suggesting di↵erent generative mechanisms. Coherence in the alpha and gamma bands was almost exclusively confined to trials showing a movement overshoot, suggesting a functional role related to error correction. We interpret the dual-band synchronization in the alpha and gamma bands as parallel streams of corticospinal processing involved in parsing prediction errors and generating new motor predictions.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The reorganization of corticomuscular coherence during a transition between sensorimotor states

2014

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“…Cortical gamma-band activity in general has been found to be involved in many cortical processes (Tallon-Baudry, 2009;Fries, 2009), and might serve as a mechanism for efficient neuronal communication and processing (Fries, 2005). Gamma activity has been related to important brain functions such as visual (Hoogenboom et al, 2006) and tactile processing (Bauer et al, 2006), memory (Jensen et al, 2007;van der Werf et al, 2008), attention (Fries et al, 2001), and motor control (Schoffelen et al, 2005).…”

Section: Eccentricity Effectmentioning

confidence: 99%

Visual stimulus eccentricity affects human gamma peak frequency

Pelt

Fries

2013

NeuroImage

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“…This observation calls for a neuronal mechanism, often referred to as binding (Treisman, 1999;Treisman and Gelade, 1980;Zimmer et al, 2006), allowing for integration of distributed information in the service of cognitive functions (e.g., Ballard et al, 1983;Barlow, 1972;Von der Malsburg, 1981). Several authors suggested that such a mechanism could be implemented in the brain via temporally synchronized firing patterns of neuronal assemblies (Engel et al, 1992;Fries, 2005;Jensen, 2006;Lisman, 2005;Singer and Gray, 1995;Singer et al, 1996). Although not undisputed (e.g., Palanca and DeAngelis, 2005;Shadlen and Movshon, 1999), the binding theory has received support from studies of intracranial recordings that revealed that groups of activated neurons tend to synchronize in the gamma-frequency band (30-100 Hz).…”

Section: Introductionmentioning

confidence: 99%

“…Regardless of the exact roles of gamma oscillations in cognitive functioning (cf. Herrmann et al, 2004;Singer and Gray, 1995;Tallon-Baudry and Bertrand, 1999, for reviews), it becomes obvious that synchronized oscillatory activity can be considered an effective and flexible communication structure on top of the less plastic anatomical structure (Fries, 2005). However, not much is known about how lifespan changes in neuroanatomy and neurochemistry during maturation, learning, and senescence affect local synchronization properties as evidenced by EEG gamma-band oscillations (cf.…”

Section: Introductionmentioning

confidence: 99%

EEG gamma-band synchronization in visual coding from childhood to old age: Evidence from evoked power and inter-trial phase locking

Werkle‐Bergner

Shing

Müller

et al. 2009

Clinical Neurophysiology

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a b s t r a c tObjective: To investigate lifespan age differences in neuronal mechanisms of visual coding in the context of perceptual discrimination. Methods: We recorded EEG from 17 children (10-12 years), 16 younger adults (20-26 years), and 17 older adults (70-76 years) during a simple choice-reaction task requiring discrimination of squares and circles of different sizes. We examined age-group differences in the effect of stimulus size on early ERP components, evoked gamma-band power, and inter-trial phase-stability in the gamma band as assessed by the phase-locking index (PLI). Results: In the absence of age differences in discrimination accuracy, we observed reliable age differences in patterns of ERP, evoked gamma power, and PLI. P1 and N1 peak amplitudes were larger and the peak latencies longer in children than in adults. Children also showed lower levels of evoked power and PLI than adults. Older adults showed smaller increments in evoked power with increasing stimulus size than younger adults, but similar amounts of phase locking for small-and medium-sized stimuli as younger adults. Conclusions: The relative importance of different coding mechanisms in early visual areas changes from childhood to old age. Due to synaptic overproduction and immature myelination, the visual system of children is less entrained by incoming information, resulting in less synchronized neuronal responses. Adults primarily rely on sparse representations formed through experience-dependent temporally synchronized neuronal interactions. In old age, senescent decline in neuronal density and neurotransmitter availability further increase the reliance on temporally synchronized processing. Significance: Findings from this study defy the notion that sensory aging consists in a reversal of sensory development in childhood, and point to a high degree of age specificity in mechanisms of visual coding.

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A mechanism for cognitive dynamics: neuronal communication through neuronal coherence

Cited by 3,788 publications

References 50 publications

The reorganization of corticomuscular coherence during a transition between sensorimotor states

The reorganization of corticomuscular coherence during a transition between sensorimotor states

Visual stimulus eccentricity affects human gamma peak frequency

EEG gamma-band synchronization in visual coding from childhood to old age: Evidence from evoked power and inter-trial phase locking

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