@Article{ koepsell_information_2008, title = {Information transmission in oscillatory neural activity}, url = {http://arxiv.org/abs/0809.4059}, doi = {doi:10.1007/s00422-008-0273-6}, abstract = {Periodic neural activity not locked to the stimulus or to motor responses is usually ignored. Here, we present new tools for modeling and quantifying the information transmission based on periodic neural activity that occurs with quasi-random phase relative to the stimulus. We propose a model to reproduce characteristic features of oscillatory spike trains, such as histograms of inter-spike intervals and phase locking of spikes to an oscillatory influence. The proposed model is based on an inhomogeneous Gamma process governed by a density function that is a product of the usual stimulus-dependent rate and a quasi-periodic function. Further, we present an analysis method generalizing the direct method {(Rieke} et al, 1999; Brenner et al, 2000) to assess the information content in such data. We demonstrate these tools on recordings from relay cells in the lateral geniculate nucleus of the cat.}, journal = {0809.4059}, author = {Kilian Koepsell and Friedrich T Sommer}, month = sep, year = {2008}, note = {Biological Cybernetics (2008) 99:403-416}, keywords = {Computer Science - Information {Theory,Quantitative} Biology - Neurons and {Cognition,Quantitative} Biology - Quantitative Methods} } @Article{ huys_fast_2007, title = {Fast Population Coding}, volume = {19}, url = {http://neco.mitpress.org/cgi/content/abstract/19/2/404}, abstract = {Uncertainty coming from the noise in its neurons and the ill-posed nature of many tasks plagues neural computations. Maybe surprisingly, many studies show that the brain manipulates these forms of uncertainty in a probabilistically consistent and normative manner, and there is now a rich theoretical literature on the capabilities of populations of neurons to implement computations in the face of uncertainty. However, one major facet of uncertainty has received comparatively little attention: time. In a dynamic, rapidly changing world, data are only temporarily relevant. Here, we analyze the computational consequences of encoding stimulus trajectories in populations of neurons. For the most obvious, simple, instantaneous encoder, the correlations induced by natural, smooth stimuli engender a decoder that requires access to information that is nonlocal both in time and across neurons. This formally amounts to a ruinous representation. We show that there is an alternative encoder that is computationally and representationally powerful in which each spike contributes independent information; it is independently decodable, in other words. We suggest this as an appropriate foundation for understanding time-varying population codes. Furthermore, we show how adaptation to temporal stimulus statistics emerges directly from the demands of simple decoding. }, number = {2}, journal = {Neural Comp.}, author = {Quentin J. M. Huys and Richard S. Zemel and Rama Natarajan and Peter Dayan}, month = feb, year = {2007}, pages = {404--441} } @Article{ singer_visual_1995, title = {Visual Feature Integration and the Temporal Correlation Hypothesis}, volume = {18}, url = {http://arjournals.annualreviews.org/doi/pdf/10.1146/annurev.ne.18.030195.003011} , number = {1}, journal = {Annual Review of Neuroscience}, author = {W. Singer and C. M Gray}, year = {1995}, pages = {555―586} } @Article{ gray_temporal_1999, title = {The Temporal Correlation Hypothesis Review of Visual Feature Integration: Still Alive and Well}, volume = {24}, url = {http://dx.doi.org/10.1016/S0896-6273(00)80820-X}, journal = {Neuron}, author = {C. M Gray}, year = {1999}, pages = {31―47} } @Article{ rajkai_transient_2008, title = {Transient Cortical Excitation at the Onset of Visual Fixation}, volume = {18}, url = {http://cercor.oxfordjournals.org/cgi/content/abstract/18/1/200} , doi = {10.1093/cercor/bhm046}, abstract = {Primates actively examine the visual world by rapidly shifting gaze (fixation) over the elements in a scene. Despite this fact, we typically study vision by presenting stimuli with gaze held constant. To better understand the dynamics of natural vision, we examined how the onset of visual fixation affects ongoing neuronal activity in the absence of visual stimulation. We used multiunit activity and current source density measurements to index neuronal firing patterns and underlying synaptic processes in macaque V1. Initial averaging of neural activity synchronized to the onset of fixation suggested that a brief period of cortical excitation follows each fixation. Subsequent single-trial analyses revealed that 1) neuronal oscillation phase transits from random to a highly organized state just after the fixation onset, 2) this phase concentration is accompanied by increased spectral power in several frequency bands, and 3) visual response amplitude is enhanced at the specific oscillatory phase associated with fixation. We hypothesize that nonvisual inputs are used by the brain to increase cortical excitability at fixation onset, thus "priming" the system for new visual inputs generated at fixation. Despite remaining mechanistic questions, it appears that analysis of fixation-related responses may be useful in studying natural vision. }, number = {1}, journal = {Cereb. Cortex}, author = {Csaba Rajkai and Peter Lakatos and {Chi-Ming} Chen and Zsuzsa Pincze and Gyorgy Karmos and Charles E. Schroeder}, year = {2008}, pages = {200--209} } @Article{ vanrullen_continuous_2006, title = {The continuous wagon wheel illusion is associated with changes in electroencephalogram power at approximately 13 Hz.}, volume = {26}, issn = {1529-2401}, url = {http://dx.doi.org/10.1523/JNEUROSCI.4654-05.2006}, abstract = {Continuously moving objects sometimes appear to spontaneously reverse their motion direction. The mechanisms underlying this bistable phenomenon (the "continuous wagon wheel illusion") are heavily debated, but one interpretation suggests that motion information is perceived in discrete episodes at a rate between 10 and 15 Hz. Here, we asked observers to report the perceived direction of a continuously rotating wheel while 32-channel electroencephalogram {(EEG)} was recorded. We then separated periods of perceived true from illusory (reversed) motion and compared the {EEG} power spectrum under these two perceptually distinct yet physically identical conditions. The only reliable difference was observed approximately 13 Hz over centroparietal electrodes, independent of the temporal frequency of the wheel. Thus, it is likely to reflect internal processes rather than purely stimulus-driven activity. {EEG} power (13 Hz) decreased before the onset of illusory motion and increased before transitions back to real motion. Using this relationship, it was possible to predict above chance, on a trial-by-trial basis, the direction of the upcoming perceptual transition. These data are compatible with the idea that motion perception occurs in snapshots {\textless}100 ms in duration.}, number = {2}, journal = {J Neurosci}, author = {R {VanRullen} and L Reddy and C Koch}, year = {2006}, keywords = {cog-neuro,eeg-components,neuro-coding,neuro-connectivity,neuro-sync,neuro-timing,perception} , pages = {507, 502} } @Article{ friedman-hill_dynamics_2000, title = {Dynamics of Striate Cortical Activity in the Alert Macaque: I. Incidence and Stimulus-dependence of Gamma-band Neuronal Oscillations}, volume = {10}, url = {http://cercor.oxfordjournals.org/cgi/content/abstract/10/11/1105} , doi = {10.1093/cercor/10.11.1105}, abstract = {Using single and multiunit recordings in the striate cortex of alert macaque monkeys, we find that gamma-band (20-70 Hz) oscillations in neuronal firing are a prominent feature of V1 neuronal activity. The properties of this rhythmic activity are very similar to those previously observed in the cat. Gamma-band activity is strongly dependent on visual stimulation, largely absent during spontaneous activity and, under the conditions of our experiment, not time-locked to the vertical refresh of the computer monitor (80 Hz) used to present the stimuli. In our sample, 61\% of multiunit activity {(MUA)} and 46\% of single-unit activity {(SUA)} was significantly oscillatory, with mean frequencies of 48 +/- 9 and 42 +/- 13 Hz, respectively. Gamma-band activity was most likely to occur when cells were activated by their optimal stimuli, but still occurred, although less often and with lower amplitude, in response to nonoptimal stimuli. The frequency of gamma-band activity also reflected stimulus properties, with drifting gratings evoking higher-frequency oscillations than stationary gratings. As in the cat, the spike trains of single cells showing gamma-band oscillations often displayed a pattern of repetitive burst firing, with intraburst firing rates of 300-800 Hz. The overall similarity of rhythmic neuronal activity in the primary visual cortex of cats and monkeys suggests that the phenomenon is not species-specific. The stimulus-dependence of the rhythmic activity is consistent with a functional role in visual perception.}, number = {11}, journal = {Cereb. Cortex}, author = {Stacia {Friedman-Hill} and Pedro E Maldonado and Charles M Gray}, year = {2000}, pages = {1105--1116} } @Article{ gray_stimulus-specific_1989, title = {{Stimulus-Specific} Neuronal Oscillations in Orientation Columns of Cat Visual Cortex}, volume = {86}, url = {http://www.pnas.org/cgi/content/abstract/86/5/1698}, doi = {10.1073/pnas.86.5.1698}, abstract = {In areas 17 and 18 of the cat visual cortex the firing probability of neurons, in response to the presentation of optimally aligned light bars within their receptive field, oscillates with a peak frequency near 40 Hz. The neuronal firing pattern is tightly correlated with the phase and amplitude of an oscillatory local field potential recorded through the same electrode. The amplitude of the local field-potential oscillations are maximal in response to stimuli that match the orientation and direction preference of the local cluster of neurons. Single and multiunit recordings from the dorsal lateral geniculate nucleus of the thalamus showed no evidence of oscillations of the neuronal firing probability in the range of 20-70 Hz. The results demonstrate that local neuronal populations in the visual cortex engage in stimulus-specific synchronous oscillations resulting from an intracortical mechanism. The oscillatory responses may provide a general mechanism by which activity patterns in spatially separate regions of the cortex are temporally coordinated.}, number = {5}, journal = {{PNAS}}, author = {Charles M Gray and Wolf Singer}, year = {1989}, pages = {1698--1702} } @Article{ canolty_high_2006, title = {High gamma power is phase-locked to theta oscillations in human neocortex.}, volume = {313}, url = {http://dx.doi.org/10.1126/science.1128115}, doi = {10.1126/science.1128115}, abstract = {We observed robust coupling between the high- and low-frequency bands of ongoing electrical activity in the human brain. In particular, the phase of the low-frequency theta (4 to 8 hertz) rhythm modulates power in the high gamma (80 to 150 hertz) band of the electrocorticogram, with stronger modulation occurring at higher theta amplitudes. Furthermore, different behavioral tasks evoke distinct patterns of theta/high gamma coupling across the cortex. The results indicate that transient coupling between low- and high-frequency brain rhythms coordinates activity in distributed cortical areas, providing a mechanism for effective communication during cognitive processing in humans.}, number = {5793}, journal = {Science}, author = {R. T. Canolty and E. Edwards and S. S. Dalal and M. Soltani and S. S. Nagarajan and H. E. Kirsch and M. S. Berger and N. M. Barbaro and R. T. Knight}, month = sep, year = {2006}, keywords = {Adult; Attention; Auditory Perception; Cognition; {Electrodes,Implanted;} Electrophysiology; Epilepsy; Female; Humans; Memory; Mental Processes; Middle Aged; Neocortex; Psychomotor Performance; Theta Rhythm; Visual Perception}, pages = {1626―1628} } @Article{ rehn_network_2007, title = {A network that uses few active neurones to code visual input predicts the diverse shapes of cortical receptive fields}, volume = {22}, url = {http://www.springerlink.com/index/T364267555HQ4031.pdf}, number = {2}, journal = {Journal of Computational Neuroscience}, author = {M. Rehn and F. T Sommer}, year = {2007}, pages = {135―146} } @Article{ rabinovich_dynamical_2006, title = {Dynamical principles in neuroscience}, volume = {78}, url = {http://link.aps.org/abstract/RMP/v78/p1213}, doi = {{10.1103/RevModPhys.78.1213}}, abstract = {Dynamical modeling of neural systems and brain functions has a history of success over the last half century. This includes, for example, the explanation and prediction of some features of neural rhythmic behaviors. Many interesting dynamical models of learning and memory based on physiological experiments have been suggested over the last two decades. Dynamical models even of consciousness now exist. Usually these models and results are based on traditional approaches and paradigms of nonlinear dynamics including dynamical chaos. Neural systems are, however, an unusual subject for nonlinear dynamics for several reasons: (i) Even the simplest neural network, with only a few neurons and synaptic connections, has an enormous number of variables and control parameters. These make neural systems adaptive and flexible, and are critical to their biological function. (ii) In contrast to traditional physical systems described by well-known basic principles, first principles governing the dynamics of neural systems are unknown. (iii) Many different neural systems exhibit similar dynamics despite having different architectures and different levels of complexity. (iv) The network architecture and connection strengths are usually not known in detail and therefore the dynamical analysis must, in some sense, be probabilistic. (v) Since nervous systems are able to organize behavior based on sensory inputs, the dynamical modeling of these systems has to explain the transformation of temporal information into combinatorial or combinatorial-temporal codes, and vice versa, for memory and recognition. In this review these problems are discussed in the context of addressing the stimulating questions: What can neuroscience learn from nonlinear dynamics, and what can nonlinear dynamics learn from neuroscience?}, number = {4}, journal = {Reviews of Modern Physics}, author = {M. I Rabinovich and P. Varona and A. I Selverston and H. {D.I} Abarbanel}, year = {2006}, pages = {1213―1265} } @Article{ kenet_spontaneously_2003, title = {Spontaneously emerging cortical representations of visual attributes.}, volume = {425}, url = {http://dx.doi.org/10.1038/nature02078}, doi = {10.1038/nature02078}, abstract = {Spontaneous cortical activity―ongoing activity in the absence of intentional sensory input―has been studied extensively, using methods ranging from {EEG} (electroencephalography), through voltage sensitive dye imaging, down to recordings from single neurons. Ongoing cortical activity has been shown to play a critical role in development, and must also be essential for processing sensory perception, because it modulates stimulus-evoked activity, and is correlated with behaviour. Yet its role in the processing of external information and its relationship to internal representations of sensory attributes remains unknown. Using voltage sensitive dye imaging, we previously established a close link between ongoing activity in the visual cortex of anaesthetized cats and the spontaneous firing of a single neuron. Here we report that such activity encompasses a set of dynamically switching cortical states, many of which correspond closely to orientation maps. When such an orientation state emerged spontaneously, it spanned several hypercolumns and was often followed by a state corresponding to a proximal orientation. We suggest that dynamically switching cortical states could represent the brain's internal context, and therefore reflect or influence memory, perception and behaviour.}, number = {6961}, journal = {Nature}, author = {Tal Kenet and Dmitri Bibitchkov and Misha Tsodyks and Amiram Grinvald and Amos Arieli}, month = oct, year = {2003}, keywords = {{Algorithms;,Anesthesia;,Animals;,Brain,Cats;,Cortex;,Dyes;,Fluorescent,Mapping;,Orientation;,Perception,Visual}} , pages = {954―956} } @Article{ singer_neuronal_1999, title = {Neuronal synchrony: a versatile code for the definition of relations?}, volume = {4(1)}, journal = {Neuron}, author = {W. Singer}, year = {1999}, pages = {49--65, 111-25} } @Article{ azouz_adaptive_2003, title = {Adaptive coincidence detection and dynamic gain control in visual cortical neurons in vivo.}, volume = {37}, url = {http://dx.doi.org/10.1016/S0896-6273(02)01186-8}, abstract = {Several theories have proposed a functional role for response synchronization in sensory perception. Critics of these theories have argued that selective synchronization is physiologically implausible when cortical networks operate at high levels of activity. Using intracellular recordings from visual cortex in vivo, in combination with numerical simulations, we find dynamic changes in spike threshold that reduce cellular sensitivity to slow depolarizations and concurrently increase the relative sensitivity to rapid depolarizations. Consistent with this, we find that spike activity and high-frequency fluctuations in membrane potential are closely correlated and that both are more tightly tuned for stimulus orientation than the mean membrane potential. These findings suggest that under high-input conditions the spike-generating mechanism adaptively enhances the sensitivity to synchronous inputs while simultaneously decreasing the sensitivity to temporally uncorrelated inputs.}, number = {3}, journal = {Neuron}, author = {Rony Azouz and Charles M Gray}, month = feb, year = {2003}, keywords = {Action Potentials; {Adaptation,Ocular;} Animals; Cats; Evoked {Potentials,Visual;} Female; Male; Neurons; Orientation; Sensory Thresholds; Visual Cortex}, pages = {513―523} } @Article{ vanrullen_spike_2005, title = {Spike times make sense.}, volume = {28}, issn = {0166-2236}, url = {http://dx.doi.org/10.1016/j.tins.2004.10.010}, abstract = {Many behavioral responses are completed too quickly for the underlying sensory processes to rely on estimation of neural firing rates over extended time windows. Theoretically, first-spike times could underlie such rapid responses, but direct evidence has been lacking. Such evidence has now been uncovered in the human somatosensory system. We discuss these findings and their potential generalization to other sensory modalities, and we consider some future challenges for the neuroscientific community.}, number = {1}, journal = {Trends Neurosci}, author = {R Vanrullen and R Guyonneau and {SJ} Thorpe}, year = {2005}, keywords = {coding,temporal}, pages = {4, 1} } @Article{ gray_oscillatory_1989, title = {Oscillatory responses in cat visual cortex exhibit inter-columnar synchronization which reflects global stimulus properties}, volume = {338}, url = {http://www.nature.com/nature/journal/v338/n6213/abs/338334a0.html} , number = {6213}, journal = {Nature}, author = {C. M Gray and P. Koenig and A. K Engel and W. Singer}, year = {1989}, pages = {334―337} } @Article{ maldonado_synchronization_2008, title = {Synchronization of Neuronal Responses in Primary Visual Cortex of Monkeys Viewing Natural Images}, volume = {100}, url = {http://jn.physiology.org/cgi/content/abstract/100/3/1523}, doi = {10.1152/jn.00076.2008}, abstract = {When inspecting visual scenes, primates perform on average four saccadic eye movements per second, which implies that scene segmentation, feature binding, and identification of image components is accomplished in {\textless}200 ms. Thus individual neurons can contribute only a small number of discharges for these complex computations, suggesting that information is encoded not only in the discharge rate but also in the timing of action potentials. While monkeys inspected natural scenes we registered, with multielectrodes from primary visual cortex, the discharges of simultaneously recorded neurons. Relating these signals to eye movements revealed that discharge rates peaked around 90 ms after fixation onset and then decreased to near baseline levels within 200 ms. Unitary event analysis revealed that preceding this increase in firing there was an episode of enhanced response synchronization during which discharges of spatially distributed cells coincided within 5-ms windows significantly more often than predicted by the discharge rates. This episode started 30 ms after fixation onset and ended by the time discharge rates had reached their maximum. When the animals scanned a blank screen a small change in firing rate, but no excess synchronization, was observed. The short latency of the stimulation-related synchronization phenomena suggests a fast-acting mechanism for the coordination of spike timing that may contribute to the basic operations of scene segmentation. }, number = {3}, journal = {J Neurophysiol}, author = {Pedro Maldonado and Cecilia Babul and Wolf Singer and Eugenio Rodriguez and Denise Berger and Sonja Grun}, month = sep, year = {2008}, pages = {1523--1532} } @Article{ fries_modulation_2001, title = {Modulation of Oscillatory Neuronal Synchronization by Selective Visual Attention}, volume = {291}, url = {http://www.sciencemag.org/cgi/content/abstract/291/5508/1560} , doi = {10.1126/science.1055465}, number = {5508}, journal = {Science}, author = {Pascal Fries and John H Reynolds and Alan E Rorie and Robert Desimone}, year = {2001}, pages = {1560--1563} } @Article{ sauseng_are_2007, title = {Are event-related potential components generated by phase resetting of brain oscillations? A critical discussion.}, issn = {0306-4522}, url = {http://dx.doi.org/10.1016/j.neuroscience.2007.03.014}, abstract = {The event-related potential {(ERP)} is one of the most popular measures in human cognitive neuroscience. During the last few years there has been a debate about the neural fundamentals of {ERPs.} Two models have been proposed: The evoked model states that additive evoked responses which are completely independent of ongoing background electroencephalogram generate the {ERP.} On the other hand the phase reset model suggests a resetting of ongoing brain oscillations to be the neural generator of {ERPs.} Here, evidence for either of the two models is presented and validated, and their possible impact on cognitive neuroscience is discussed. In addition, future prospects on this field of research are presented.}, journal = {Neuroscience}, author = {P Sauseng and W Klimesch and W R Gruber and S Hanslmayr and R Freunberger and M Doppelmayr}, month = apr, year = {2007}, keywords = {eeg,erp,heather,kristina,yigal} } @Article{ tsodyks_linking_1999, title = {Linking spontaneous activity of single cortical neurons and the underlying functional architecture.}, volume = {286}, url = {http://www.sciencemag.org/cgi/content/abstract/286/5446/1943} , abstract = {The relation between the activity of a single neocortical neuron and the dynamics of the network in which it is embedded was explored by single-unit recordings and real-time optical imaging. The firing rate of a spontaneously active single neuron strongly depends on the instantaneous spatial pattern of ongoing population activity in a large cortical area. Very similar spatial patterns of population activity were observed both when the neuron fired spontaneously and when it was driven by its optimal stimulus. The evoked patterns could be used to reconstruct the spontaneous activity of single neurons.}, number = {5446}, journal = {Science}, author = {M. Tsodyks and T. Kenet and A. Grinvald and A. Arieli}, month = dec, year = {1999}, keywords = {Action Potentials; Animals; Brain Mapping; Cats; Evoked {Potentials,Computer-Assisted;} Nerve Net; Neurons; {Patch-Clamp} Techniques; Photic Stimulation; Visual Cortex; Visual {Pathways,Visual;} Image Processing}, pages = {1943―1946} } @Article{ min_best_2007, title = {The best of both worlds: phase-reset of human {EEG} alpha activity and additive power contribute to {ERP} generation}, volume = {65}, issn = {0167-8760}, url = {http://www.ncbi.nlm.nih.gov/pubmed/17428561}, doi = {10.1016/j.ijpsycho.2007.03.002}, abstract = {Some authors have proposed that event-related potentials {(ERPs)} are generated by a neuronal response which is additive to and independent of ongoing activity, others demonstrated that they are generated by partial phase-resetting of ongoing activity. We investigated the relationship between event-related oscillatory activity in the alpha band and prestimulus levels of ongoing alpha activity on {ERPs.} {EEG} was recorded from 23 participants performing a visual discrimination task. Individuals were assigned to one of three groups according to the amount of prestimulus total alpha activity, and distinct differences of the event-related {EEG} dynamics between groups were observed. While all groups exhibited an event-related increase in phase-locked (evoked) alpha activity, only individuals with sustained prestimulus alpha activity showed alpha-blocking, that is, a considerable decrease of poststimulus non-phase-locked alpha activity. In contrast, individuals without observable prestimulus total alpha activity showed a concurrent increase of phase-locked and non-phase-locked alpha activity after stimulation. Data from this group seems to be in favor of an additive event-related neuronal response without alpha-blocking. However, the dissociable {EEG} dynamics of total and evoked alpha activities together with a complementary simulation analysis indicated a partial event-related reorganization of ongoing brain activity. We conclude that both partial phase-resetting and partial additive power contribute dynamically to the generation of {ERPs.} The prestimulus brain state exerts a prominent influence on event-related brain responses.}, number = {1}, journal = {International Journal of Psychophysiology: Official Journal of the International Organization of Psychophysiology}, author = {{Byoung-Kyong} Min and Niko A Busch and Stefan Debener and Cornelia Kranczioch and Simon Hanslmayr and Andreas K Engel and Christoph S Herrmann}, month = jul, year = {2007}, note = {{PMID:} 17428561}, keywords = {{Adult,Alpha} {Rhythm,Data} Interpretation, {Statistical,Discrimination} {(Psychology),Evoked} {Potentials,Female,Humans,Male,Models,} {Neurological,Psychomotor} {Performance,Visual} Perception}, pages = {58--68} } @Article{ fries_finding_2008, title = {Finding gamma}, volume = {58}, issn = {1097-4199}, url = {http://www.ncbi.nlm.nih.gov/pubmed/18466741}, doi = {10.1016/j.neuron.2008.04.020}, abstract = {Neuronal gamma-band synchronization is central for cognition. Respective studies in human subjects focused on a visually induced transient enhancement of broadband {EEG} power. In this issue of Neuron, {Yuval-Greenberg} et al. demonstrate that this {EEG} response is an artifact of microsaccades, raising the question of whether gamma-band synchronization can be assessed with {EEG.}}, number = {3}, journal = {Neuron}, author = {Pascal Fries and René Scheeringa and Robert Oostenveld}, month = may, year = {2008}, note = {{PMID:} 18466741}, keywords = {{Animals,Artifacts,Cognition,Electroencephalography,Evoked} Potentials, {Visual,Humans,Saccades}}, pages = {303--5} } @Article{ vanrullen_is_2003, title = {Is perception discrete or continuous?}, volume = {7}, issn = {1364-6613}, url = {http://view.ncbi.nlm.nih.gov/pubmed/12757822}, abstract = {How does conscious perception evolve following stimulus presentation? The idea that perception relies on discrete processing epochs has been often considered, but never widely accepted. The alternative, a continuous translation of the external world into explicit perception, although more intuitive and subjectively appealing, cannot satisfactorily account for a large body of psychophysical data. Cortical and thalamocortical oscillations in different frequency bands could provide a neuronal basis for such discrete processes, but are rarely analyzed in this context. This article reconciles the unduly abandoned topic of discrete perception with current views and advances in neuroscience.}, number = {5}, journal = {Trends in cognitive sciences}, author = {Rufin {VanRullen} and Christof Koch}, month = may, year = {2003}, keywords = {discreteprocessing,lfpproject,sniffproject}, pages = {213, 207} } @Article{ fries_gamma_2007, title = {The gamma cycle.}, volume = {30}, url = {http://dx.doi.org/10.1016/j.tins.2007.05.005}, doi = {10.1016/j.tins.2007.05.005}, abstract = {Activated neuronal groups typically engage in rhythmic synchronization in the gamma-frequency range (30-100 Hz). Experimental and modeling studies demonstrate that each gamma cycle is framed by synchronized spiking of inhibitory interneurons. Here, we review evidence suggesting that the resulting rhythmic network inhibition interacts with excitatory input to pyramidal cells such that the more excited cells fire earlier in the gamma cycle. Thus, the amplitude of excitatory drive is recoded into phase values of discharges relative to the gamma cycle. This recoding enables transmission and read out of amplitude information within a single gamma cycle without requiring rate integration. Furthermore, variation of phase relations can be exploited to facilitate or inhibit exchange of information between oscillating cell assemblies. The gamma cycle could thus serve as a fundamental computational mechanism for the implementation of a temporal coding scheme that enables fast processing and flexible routing of activity, supporting fast selection and binding of distributed responses. This review is part of the {INMED/TINS} special issue Physiogenic and pathogenic oscillations: the beauty and the beast, based on presentations at the annual {INMED/TINS} symposium (http://inmednet.com).}, number = {7}, journal = {Trends Neurosci}, author = {Pascal Fries and Danko Nikolić and Wolf Singer}, month = jul, year = {2007}, pages = {309―316} } @Article{ yuval-greenberg_transient_2008, title = {Transient Induced {Gamma-Band} Response in {EEG} as a Manifestation of Miniature Saccades}, volume = {58}, issn = {0896-6273}, url = {http://www.sciencedirect.com/science/article/B6WSS-4SFRCHN-H/2/2f109e607058681a8bddd836c44e1751} , doi = {10.1016/j.neuron.2008.03.027}, abstract = {Summary The induced gamma-band {EEG} response {(iGBR)} recorded on the scalp is widely assumed to reflect synchronous neural oscillation associated with object representation, attention, memory, and consciousness. The most commonly reported {EEG} {iGBR} is a broadband transient increase in power at the gamma range {\textasciitilde}200-300 ms following stimulus onset. A conspicuous feature of this {iGBR} is the trial-to-trial poststimulus latency variability, which has been insufficiently addressed. Here, we show, using single-trial analysis of concomitant {EEG} and eye tracking, that this {iGBR} is tightly time locked to the onset of involuntary miniature eye movements and reflects a saccadic "spike potential." The time course of the {iGBR} is related to an increase in the rate of saccades following a period of poststimulus saccadic inhibition. Thus, whereas neuronal gamma-band oscillations were shown conclusively with other methods, the broadband transient {iGBR} recorded by scalp {EEG} reflects properties of miniature saccade dynamics rather than neuronal oscillations.}, number = {3}, journal = {Neuron}, author = {Shlomit {Yuval-Greenberg} and Orr Tomer and Alon S. Keren and Israel Nelken and Leon Y. Deouell}, month = may, year = {2008}, keywords = {{SYSBIO,SYSNEURO}}, pages = {429--441} } @Article{ blanche_polytrodes:_2005, title = {Polytrodes: high-density silicon electrode arrays for large-scale multiunit recording}, volume = {93}, issn = {0022-3077}, url = {http://www.ncbi.nlm.nih.gov/pubmed/15548620}, doi = {01023.2004}, abstract = {We developed a variety of 54-channel high-density silicon electrode arrays (polytrodes) designed to record from large numbers of neurons spanning millimeters of brain. In cat visual cortex, it was possible to make simultaneous recordings from {\textgreater}100 well-isolated neurons. Using standard clustering methods, polytrodes provide a quality of single-unit isolation that surpasses that attainable with tetrodes. Guidelines for successful in vivo recording and precise electrode positioning are described. We also describe a high-bandwidth continuous data-acquisition system designed specifically for polytrodes and an automated impedance meter for testing polytrode site integrity. Despite having smaller interconnect pitches than earlier silicon-based electrodes of this type, these polytrodes have negligible channel crosstalk, comparable reliability, and low site impedances and are capable of making high-fidelity multiunit recordings with minimal tissue damage. The relatively benign nature of planar electrode arrays is evident both histologically and in experiments where the polytrode was repeatedly advanced and retracted hundreds of microns over periods of many hours. It was possible to maintain stable recordings from active neurons adjacent to the polytrode without change in their absolute positions, neurophysiological or receptive field properties.}, number = {5}, journal = {Journal of Neurophysiology}, author = {Timothy J Blanche and Martin A Spacek and Jamille F Hetke and Nicholas V Swindale}, month = may, year = {2005}, note = {{PMID:} 15548620}, keywords = {Action {Potentials,Animals,Brain} {Mapping,Carbocyanines,Cats,Computer} {Simulation,Densitometry,Electric} {Conductivity,Electric} {Impedance,Electric} {Stimulation,Electrodes,} {Implanted,Electrophysiology,Evoked} {Potentials,Microelectrodes,Online} {Systems,Rats,Research} {Design,Silicon,Time,Visual} Cortex}, pages = {2987--3000} } @Article{ fries_mechanism_2005, title = {A mechanism for cognitive dynamics: neuronal communication through neuronal coherence.}, volume = {9}, url = {http://dx.doi.org/10.1016/j.tics.2005.08.011}, doi = {10.1016/j.tics.2005.08.011}, abstract = {At any one moment, many neuronal groups in our brain are active. Microelectrode recordings have characterized the activation of single neurons and {fMRI} has unveiled brain-wide activation patterns. Now it is time to understand how the many active neuronal groups interact with each other and how their communication is flexibly modulated to bring about our cognitive dynamics. I hypothesize that neuronal communication is mechanistically subserved by neuronal coherence. Activated neuronal groups oscillate and thereby undergo rhythmic excitability fluctuations that produce temporal windows for communication. Only coherently oscillating neuronal groups can interact effectively, because their communication windows for input and for output are open at the same times. Thus, a flexible pattern of coherence defines a flexible communication structure, which subserves our cognitive flexibility.}, number = {10}, journal = {Trends Cogn Sci}, author = {Pascal Fries}, month = oct, year = {2005}, keywords = {{Action,Animals;,Biological,Brain;,Clocks;,Cognition;,Dynamics;,Humans;,Nerve,Net;,Neurons;,Nonlinear,Periodicity;,Potentials;,Pyramidal,Synaptic,Tracts;,Transmission}} , pages = {474―480} } @Article{ guyonneau_temporal_2004, title = {Temporal codes and sparse representations: A key to understanding rapid processing in the visual system}, volume = {98}, issn = {0928-4257}, url = {http://www.sciencedirect.com/science/article/B6VMC-4HGM76C-1/2/6cf4b835b1da9a3bddd0603e8d72cc08} , doi = {10.1016/j.jphysparis.2005.09.004}, abstract = { Where neural information processing is concerned, there is no debate about the fact that spikes are the basic currency for transmitting information between neurons. How the brain actually uses them to encode information remains more controversial. It is commonly assumed that neuronal firing rate is the key variable, but the speed with which images can be analysed by the visual system poses a major challenge for rate-based approaches. We will thus expose here the possibility that the brain makes use of the spatio-temporal structure of spike patterns to encode information. We then consider how such rapid selective neural responses can be generated rapidly through spike-timing-dependent plasticity {(STDP)} and how these selectivities can be used for visual representation and recognition. Finally, we show how temporal codes and sparse representations may very well arise one from another and explain some of the remarkable features of processing in the visual system.}, number = {4-6}, journal = {Journal of {Physiology-Paris}}, author = {Rudy Guyonneau and Rufin {VanRullen} and Simon J. Thorpe}, year = {2004}, keywords = {Learning, {STDP,Sparse} {representations,Temporal} {codes,Visual} processing}, pages = {487--497} } @Article{ vanrullen_surfingspike_2002, title = {Surfing a spike wave down the ventral stream}, volume = {42}, url = {http://dx.doi.org/10.1016/S0042-6989(02)00298-5}, number = {23}, journal = {Vision Research}, author = {Rufin Vanrullen and Simon Thorpe}, month = oct, year = {2002}, pages = {2615, 2593} }