Giraud Cortical oscillations and sensory predictions Trends Cogn. Sci., 16 (7) (2012), pp. 390-398, 10.1016/j.tics.2012.05.003 View PDFView articleView in ScopusGoogle Scholar Arnal et al., 2011 L.H. Arnal, V.
Communication between neocortex and hippocampus during sleep in rodents. Proc. Natl. Acad. Sci. USA 100, 2065–2069 (2003). Article CAS PubMed PubMed Central Google Scholar Arnal, L.H. & Giraud, A.-L. Cortical oscillations and sensory predictions. Trends Cogn. Sci. 16, 390–398 (2012...
Two largely distinct bodies of research have demonstrated age-related alterations and disease-specific aberrations in both local gamma oscillations and patterns of cortical thickness. However, seldom has the relationship between gamma activity and cortical thickness been investigated. Herein, we combine the...
Cortical state, defined by population-level neuronal activity patterns, determines sensory perception. While arousal-associated neuromodulators—including norepinephrine (NE)—reduce cortical synchrony, how the cortex resynchronizes remains unknown. Furthermore, general mechanisms regulating cortical synchrony in...
Sensory cortices display a suite of ubiquitous dynamical features, such as ongoing noise variability, transient overshoots, and oscillations, that have so far escaped a common, principled theoretical account. We developed a unifying model for these phenomena by training a recurrent excitatory-inhibitory...
Neuronal oscillations are commonly analyzed with power spectral methods that quantify signal amplitude, but not rhythmicity or ‘oscillatoriness’ per se. Here we introduce a new approach, the phase-autocorrelation function (pACF), for the direct quantif
Ahissar, E., Haidarliu, S., and Zacksenhouse, M.: 1997, Decoding temporally encoded sensory input by cortical oscillations and thalamic phase comparators, Proc. Natl. Acad. Sci. (USA) 94(21), 11633-11638.Ahissar, E., Haidarliu, S., and Zacksenhouse, M. (1997). Decoding temporally...
To understand the role of sleep in maintaining an optimal computational regime in the brain under normal conditions, we monitored circuit activity for extended periods, capitalizing on variations in behavior and environment to test fundamental predictions about network set points. We continuously recorded...
The neural mechanisms underlying conscious recognition remain unclear, particularly the roles played by the prefrontal cortex, deactivated brain areas and subcortical regions. We investigated neural activity during conscious object recognition using 7 Te
Sleep is characterized by a structured combination of neuronal oscillations. In the hippocampus, slow-wave sleep (SWS) is marked by high-frequency network oscillations (∼200 Hz “ripples”), whereas neocortical SWS activity is organized into low-frequency delta (1–4 Hz) and spindle (7–14 ...