Gamma Range Oscillations Research Articles

Imaging high-frequency voltage dynamics in multiple neuron classes of behaving mammals.

Fluorescent genetically encoded voltage indicators report transmembrane potentials of targeted cell-types. However, voltage-imaging instrumentation has lacked the sensitivity to track spontaneous or evoked high-frequency voltage oscillations in neural populations. Here we describe two complementary TEMPO voltage-sensing technologies that capture neural oscillations up to ~100 Hz. Fiber-optic TEMPO achieves ~10-fold greater sensitivity than prior photometry systems, allows hour-long recordings, and monitors two neuron-classes per fiber-optic probe in freely moving mice. With it, we uncovered cross-frequency-coupled theta- and gamma-range oscillations and characterized excitatory-inhibitory neural dynamics during hippocampal ripples and visual cortical processing. The TEMPO mesoscope images voltage activity in two cell-classes across a ~8-mm-wide field-of-view in head-fixed animals. In awake mice, it revealed sensory-evoked excitatory-inhibitory neural interactions and traveling gamma and 3-7 Hz waves in the visual cortex, and previously unreported propagation directions for hippocampal theta and beta waves. These technologies have widespread applications probing diverse oscillations and neuron-type interactions in healthy and diseased brains.

Prefrontal Oscillatory Slowing in Early-Course Schizophrenia Is Associated With Worse Cognitive Performance and Negative Symptoms: A Transcranial Magnetic Stimulation-Electroencephalography Study

BackgroundAbnormalities in dorsolateral prefrontal cortex (DLPFC) oscillations are neurophysiological signatures of schizophrenia thought to underlie its cognitive deficits. Transcranial magnetic stimulation with electroencephalography (TMS-EEG) provides a measure of cortical oscillations unaffected by sensory relay functionality and/or patients’ level of engagement, which are important confounding factors in schizophrenia. Previous TMS–EEG work showed reduced fast, gamma-range oscillations and a slowing of the main DLPFC oscillatory frequency, or natural frequency, in chronic schizophrenia. However, it is unclear whether this DLPFC natural frequency slowing is present in early-course schizophrenia (EC-SCZ) and is associated with symptom severity and cognitive dysfunction. MethodsWe applied TMS–EEG to the left DLPFC in 30 individuals with EC-SCZ and 28 healthy control participants. Goal-directed working memory performance was assessed using the AX–Continuous Performance Task. The EEG frequency with the highest cumulative power at the stimulation site, or natural frequency, was extracted. We also calculated the local relative spectral power as the average power in each frequency band divided by the broadband power. ResultsCompared with the healthy control group, the EC-SCZ group had reduced DLPFC natural frequency (p = .0000002, Cohen’s d = −2.32) and higher DLPFC beta-range relative spectral power (p = .0003, Cohen’s d = 0.77). In the EC-SCZ group, the DLPFC natural frequency was inversely associated with negative symptoms. Across all participants, the beta band relative spectral power negatively correlated with AX–Continuous Performance Task performance. ConclusionsDLPFC oscillatory slowing is an early pathophysiological biomarker of schizophrenia that is associated with its symptom severity and cognitive impairments. Future work should assess whether noninvasive neurostimulation, including repetitive TMS, can ameliorate prefrontal oscillatory deficits and related clinical functions in patients with EC-SCZ.

Auditory Competition and Coding of Relative Stimulus Strength across Midbrain Space Maps of Barn Owls.

The natural environment challenges the brain to prioritize the processing of salient stimuli. The barn owl, a sound localization specialist, exhibits a circuit called the midbrain stimulus selection network, dedicated to representing locations of the most salient stimulus in circumstances of concurrent stimuli. Previous competition studies using unimodal (visual) and bimodal (visual and auditory) stimuli have shown that relative strength is encoded in spike response rates. However, open questions remain concerning auditory-auditory competition on coding. To this end, we present diverse auditory competitors (concurrent flat noise and amplitude-modulated noise) and record neural responses of awake barn owls of both sexes in subsequent midbrain space maps, the external nucleus of the inferior colliculus (ICx) and optic tectum (OT). While both ICx and OT exhibit a topographic map of auditory space, OT also integrates visual input and is part of the global-inhibitory midbrain stimulus selection network. Through comparative investigation of these regions, we show that while increasing strength of a competitor sound decreases spike response rates of spatially distant neurons in both regions, relative strength determines spike train synchrony of nearby units only in the OT. Furthermore, changes in synchrony by sound competition in the OT are correlated to gamma range oscillations of local field potentials associated with input from the midbrain stimulus selection network. The results of this investigation suggest that modulations in spiking synchrony between units by gamma oscillations are an emergent coding scheme representing relative strength of concurrent stimuli, which may have relevant implications for downstream readout.

Orientation of Temporal Interference for Non-invasive Deep Brain Stimulation in Epilepsy.

In patients with focal drug-resistant epilepsy, electrical stimulation from intracranial electrodes is frequently used for the localization of seizure onset zones and related pathological networks. The ability of electrically stimulated tissue to generate beta and gamma range oscillations, called rapid-discharges, is a frequent indication of an epileptogenic zone. However, a limit of intracranial stimulation is the fixed physical location and number of implanted electrodes, leaving numerous clinically and functionally relevant brain regions unexplored. Here, we demonstrate an alternative technique relying exclusively on non-penetrating surface electrodes, namely an orientation-tunable form of temporally interfering (TI) electric fields to target the CA3 of the mouse hippocampus which focally evokes seizure-like events (SLEs) having the characteristic frequencies of rapid-discharges, but without the necessity of the implanted electrodes. The orientation of the topical electrodes with respect to the orientation of the hippocampus is demonstrated to strongly control the threshold for evoking SLEs. Additionally, we demonstrate the use of Pulse-width-modulation of square waves as an alternative to sine waves for TI stimulation. An orientation-dependent analysis of classic implanted electrodes to evoke SLEs in the hippocampus is subsequently utilized to support the results of the minimally invasive temporally interfering fields. The principles of orientation-tunable TI stimulation seen here can be generally applicable in a wide range of other excitable tissues and brain regions, overcoming several limitations of fixed electrodes which penetrate tissue and overcoming several limitations of other non-invasive stimulation methods in epilepsy, such as transcranial magnetic stimulation (TMS).

The Role of Parvalbumin-positive Interneurons in Auditory Steady-State Response Deficits in Schizophrenia

Despite an increasing body of evidence demonstrating subcellular alterations in parvalbumin-positive (PV+) interneurons in schizophrenia, their functional consequences remain elusive. Since PV+ interneurons are involved in the generation of fast cortical rhythms, these changes have been hypothesized to contribute to well-established alterations of beta and gamma range oscillations in patients suffering from schizophrenia. However, the precise role of these alterations and the role of different subtypes of PV+ interneurons is still unclear. Here we used a computational model of auditory steady-state response (ASSR) deficits in schizophrenia. We investigated the differential effects of decelerated synaptic dynamics, caused by subcellular alterations at two subtypes of PV+ interneurons: basket cells and chandelier cells. Our simulations suggest that subcellular alterations at basket cell synapses rather than chandelier cell synapses are the main contributor to these deficits. Particularly, basket cells might serve as target for innovative therapeutic interventions aiming at reversing the oscillatory deficits.

Multifactorial Modeling of Impairment of Evoked Gamma Range Oscillations in Schizophrenia.

Despite a significant increase in efforts to identify biomarkers and endophenotypic measures of psychiatric illnesses, only a very limited amount of computational models of these markers and measures has been implemented so far. Moreover, existing computational models dealing with biomarkers typically only examine one possible mechanism in isolation, disregarding the possibility that other combinations of model parameters might produce the same network behavior (what has been termed “multifactoriality”). In this study we describe a step toward a computational instantiation of an endophenotypic finding for schizophrenia, namely the impairment of evoked auditory gamma and beta oscillations in schizophrenia. We explore the multifactorial nature of this impairment using an established model of primary auditory cortex, by performing an extensive search of the parameter space. We find that single network parameters contain only little information about whether the network will show impaired gamma entrainment and that different regions in the parameter space yield similar network level oscillation abnormalities. These regions in the parameter space, however, show strong differences in the underlying network dynamics. To sum up, we present a first step toward an in silico instantiation of an important biomarker of schizophrenia, which has great potential for the identification and study of disease mechanisms and for understanding of existing treatments and development of novel ones.

Modelling impairment of evoked gamma range oscillations in schizophrenia

© 2015 Metzner et al. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Stability of fast oscillations in the mammalian olfactory bulb: Experiments and modeling

In the rat olfactory bulb (OB), fast oscillations of the local field potential (LFP) are observed during the respiratory cycle. Gamma-range oscillations (40–90 Hz) occur at the end of inspiration, followed by beta-range oscillations (15–30 Hz) during exhalation. These oscillations are highly stereotypical, and their frequencies are stable under various conditions. In this study, we investigate the effect of stimulus intensity on activity in the OB. Using a double-cannulation protocol, we showed that although the frequency of the LFP oscillation does depend on the respiratory cycle phase, it is relatively independent of the intensity of odorant stimulation. In contrast, we found that the individual firing rate of mitral OB cells dramatically changed with the intensity of the stimulation. This suggests that OB fast oscillation parameters, particularly frequency, are fully determined by intrinsic OB network parameters. To test this hypothesis, we explored a model of the OB where fast oscillations are generated by the interplay between excitatory mitral/tufted cells and inhibitory granule cells with graded inhibition. We found that our model has two distinct activity regimes depending on the amount of noise. In a low-noise regime, the model displays oscillation in the beta range with a stable frequency across a wide range of excitatory inputs. In a high-noise regime, the model displays oscillatory dynamics with irregular cell discharges and fast oscillations, similar to what is observed during gamma oscillations but without stability of the oscillation frequency with respect to the network external input. Simulations of the full model and theoretical studies of the network’s linear response show that the characteristics of the low-noise regime are induced by non-linearities in the model, notably, the saturation of graded inhibition. Finally, we discuss how this model can account for the experimentally observed stability of the oscillatory regimes.

Cortical dynamics during naturalistic sensory stimulations: Experiments and models

We report the results of our experimental and theoretical investigations of the neural response dynamics in primary visual cortex (V1) during naturalistic visual stimulation. We recorded Local Field Potentials (LFPs) and spiking activity from V1 of anaesthetized macaques during binocular presentation of Hollywood color movies. We analyzed these recordings with information theoretic methods, and found that visual information was encoded mainly by two bands of LFP responses: the network fluctuations measured by the phase and power of low-frequency (less than 12 Hz) LFPs; and fast gamma-range (50–100 Hz) oscillations. Both the power and phase of low frequency LFPs carried information largely complementary to that carried by spikes, whereas gamma range oscillations carried information largely redundant to that of spikes. To interpret these results within a quantitative theoretical framework, we then simulated a sparsely connected recurrent network of excitatory and inhibitory neurons receiving slowly varying naturalistic inputs, and we determined how the LFPs generated by the network encoded information about the inputs. We found that this simulated recurrent network reproduced well the experimentally observed dependency of LFP information upon frequency. This network encoded the overall strength of the input into the power of gamma-range oscillations generated by inhibitory–excitatory neural interactions, and encoded slow variations in the input by entraining the network LFP at the corresponding frequency. This dynamical behavior accounted quantitatively for the independent information carried by high and low frequency LFPs, and for the experimentally observed cross-frequency coupling between phase of slow LFPs and the power of gamma LFPs. We also present new results showing that the model’s dynamics also accounted for the extra visual information that the low-frequency LFP phase of spike firing carries beyond that carried by spike rates. Overall, our results suggest biological mechanisms by which cortex can multiplex information about naturalistic sensory environments.

The neural correlates of BCI performance variations in ALS: a pilot study

Event Abstract Back to Event The neural correlates of BCI performance variations in ALS: a pilot study Moritz Grosse-Wentrup1* 1 Max Planck Institute for Intelligent Systems, Empirical Inference, Germany Brain-Computer Interfaces (BCIs) hold the promise of enabling completely locked-in subjects, e.g., those in late stages of amyotrophic lateral sclerosis (ALS), to communicate by pure thought. To date, this promise has not been fulfilled. While healthy subjects and subjects in early to middle stages of ALS can learn how to operate a non-invasive BCI (Grosse-Wentrup et al., IEEE Transactions on Biomedical Engineering 56(4), 2009; Kübler et al., Neurology (64), 2005), no successful communication with a completely locked-in patient has been reported in literature. We believe that in order to enable completely locked-in patients to operate a BCI, we first need to understand the neuro-physiological causes of good and bad BCI performance. These insights might then be used induce a state-of-mind that is beneficial for operating a BCI, e.g., by neuro-feedback or electrical stimulation. In a series of recent studies, we have investigated the neuro-physiological causes of performance variations in healthy subjects operating a binary motor-imagery BCI. We found that gamma-range oscillations (between 55-85 Hz) modulate the sensorimotor-rhythm (Grosse-Wentrup et al., NeuroImage 56(2), 2011), resulting in group-average decoding differences of up to 22.2% depending on the state of fronto-parietal gamma-power (Grosse-Wentrup, 5th IEEE/EMBS International Conference on Neural Engineering, 2011). Here, we report results of a pilot study that reproduces this effect in one ALS patient. We recorded a 128-channel EEG in an ALS patient performing motor-imagery of the left or right hand. The patient was artificially ventilated, with residual control of the right wrist. We trained a support vector machine in classifying left- vs. right hand motor imagery, based on bandpower features over sensorimotor-areas. This resulted in a cross-validated accuracy of 59.2%, which is sufficient to reject the null-hypothesis of chance-level performance with p = 0.0178 (N=120). To identify brain areas related to BCI-performance, we first performed an Independent Component Analysis, manually rejected independent components (ICs) representing artifactual muscle activity, and then correlated gamma-power of the remaining ICs with a trial-wise measure of motor-imagery performance (cf. Grosse-Wentrup et al. (2011) for a description of this performance measure). In this way, we identified two ICs whose gamma-power exhibited a strong negative correlation with BCI-performance (rho = -0.3161/-0.2888, p = 0.0180/0.0258 (corrected for multiple comparisons), N = 120). A subsequent source localization procedure identified the origin of these gamma-range oscillations in the right superior parietal lobule, consistent with our findings in healthy subjects. While it remains to be seen how consistently this effect can be reproduced in ALS, its investigation over the course of ALS progression may provide novel insights into the current failure of completely locked-in patients to communicate by means of a BCI. Keywords: Amyotrophic Lateral Sclerosis, Motor Imagery, Neurotechnology and brain-machine interface Conference: BC11 : Computational Neuroscience & Neurotechnology Bernstein Conference & Neurex Annual Meeting 2011, Freiburg, Germany, 4 Oct - 6 Oct, 2011. Presentation Type: Poster Topic: neurotechnology and brain-machine interface (please use "neurotechnology and brain-machine interface" as keyword) Citation: Grosse-Wentrup M (2011). The neural correlates of BCI performance variations in ALS: a pilot study. Front. Comput. Neurosci. Conference Abstract: BC11 : Computational Neuroscience & Neurotechnology Bernstein Conference & Neurex Annual Meeting 2011. doi: 10.3389/conf.fncom.2011.53.00117 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 23 Aug 2011; Published Online: 04 Oct 2011. * Correspondence: Dr. Moritz Grosse-Wentrup, Max Planck Institute for Intelligent Systems, Empirical Inference, Tübingen, 72076, Germany, moritz.grosse-wentrup@tuebingen.mpg.de Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Moritz Grosse-Wentrup Google Moritz Grosse-Wentrup Google Scholar Moritz Grosse-Wentrup PubMed Moritz Grosse-Wentrup Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

Encoding of Naturalistic Stimuli by Local Field Potential Spectra in Networks of Excitatory and Inhibitory Neurons

Recordings of local field potentials (LFPs) reveal that the sensory cortex displays rhythmic activity and fluctuations over a wide range of frequencies and amplitudes. Yet, the role of this kind of activity in encoding sensory information remains largely unknown. To understand the rules of translation between the structure of sensory stimuli and the fluctuations of cortical responses, we simulated a sparsely connected network of excitatory and inhibitory neurons modeling a local cortical population, and we determined how the LFPs generated by the network encode information about input stimuli. We first considered simple static and periodic stimuli and then naturalistic input stimuli based on electrophysiological recordings from the thalamus of anesthetized monkeys watching natural movie scenes. We found that the simulated network produced stimulus-related LFP changes that were in striking agreement with the LFPs obtained from the primary visual cortex. Moreover, our results demonstrate that the network encoded static input spike rates into gamma-range oscillations generated by inhibitory–excitatory neural interactions and encoded slow dynamic features of the input into slow LFP fluctuations mediated by stimulus–neural interactions. The model cortical network processed dynamic stimuli with naturalistic temporal structure by using low and high response frequencies as independent communication channels, again in agreement with recent reports from visual cortex responses to naturalistic movies. One potential function of this frequency decomposition into independent information channels operated by the cortical network may be that of enhancing the capacity of the cortical column to encode our complex sensory environment.

Perisaccadic Parietal and Occipital Gamma Power in Light and in Complete Darkness

Our objective was to determine perisaccadic gamma range oscillations in the EEG during voluntary saccades in humans. We evaluated occipital perisaccadic gamma activity both in the presence and absence of visual input, when the observer was blindfolded. We quantified gamma power in the time periods before, during, and after horizontal saccades. The corresponding EEG was evaluated for individual saccades and the wavelet transformed EEG averaged for each time window, without averaging the EEG first. We found that, in both dark and light, parietal and occipital gamma power increased during the saccade and peaked prior to reaching new fixation. We show that this is not the result of muscle activity and not the result of visual input during saccades. Saccade direction affects the laterality of gamma power over posterior electrodes. Gamma power recorded over the posterior scalp increases during a saccade. The phasic modulation of gamma by saccades in darkness--when occipital activity is decoupled from visual input--provides electrophysiological evidence that voluntary saccades affect ongoing EEG. We suggest that saccade-phasic gamma modulation may contribute to short-term plasticity required to realign the visual space to the intended fixation point of a saccade and provides a mechanism for neuronal assembly formation prior to achieving the intended saccadic goal. The wavelet-transformed perisaccadic EEG could provide an electrophysiological tool applicable in humans for the purpose of fine analysis and potential separation of stages of 'planning' and 'action'.

Gamma Band Oscillations Reveal Neural Network Cortical Coherence Dysfunction in Schizophrenia Patients

Gamma band activity has been associated with many sensory and cognitive functions, and is important for cortico-cortical transmission and the integration of information across neural networks. The aims of the present study were to determine if schizophrenia patients have deficits in the generation and maintenance of coherent, synchronized oscillations in response to steady-state stimulation, and to examine the clinical and cognitive correlates of the electroencephalography (EEG) oscillatory dynamics. Schizophrenia patients (n = 100) and nonpsychiatric subjects (n = 80) underwent auditory steady-state event-related potential testing. Click trains varying in rate of stimulation (20, 30, and 40 Hz) were presented; EEG-evoked power and intertrial phase synchronization were obtained in response to each stimulation frequency. Subjects also underwent clinical and neurocognitive assessments. Patients had reductions in both evoked power and phase synchronization in response to 30- and 40-Hz stimulation but normal responsivity to 20-Hz stimulation. Maximal deficits were detected in response to 40-Hz stimulation. A modest association of reduced working memory performance and 40-Hz intertrial phase synchronization was present in schizophrenia patients (r = .32, p <.01). Schizophrenia patients have frequency-specific deficits in the generation and maintenance of coherent gamma-range oscillations, reflecting a fundamental degradation of basic integrated neural network activity.

Visual masking as a probe for abnormal gamma range activity in schizophrenia

Background Visual masking procedures assess very early stages of visual perception. Patients with schizophrenia consistently show deficits on visual masking tasks, and these deficits likely reflect vulnerability to schizophrenia. We conducted two experiments to determine whether visual masking procedures can reveal underlying abnormalities in gamma range oscillations in schizophrenia. Methods In the first experiment, we conducted nonlinear modeling of visual masking performance data from 89 male schizophrenic patients and 20 male comparison subjects. In the second experiment, electrophysiological recordings of event-related gamma activity were taken during a visual masking task in a subset of eight patients and seven control subjects. Results In the first experiment, nonlinear modeling of the performance data revealed evidence of oscillations in the gamma range (30 and 35 Hz) for the comparison group but not patients. In the second experiment, the comparison group, but not the patients, showed a burst of gamma range activity 200–400 msec following target presentation. The difference between patients and comparison subjects in this time period was significant ( p < .05). Conclusions Visual masking procedures can serve as a probe for underlying gamma range activity, which appears to be aberrant in schizophrenia. Perceptual problems in schizophrenia may, at least in part, be due to a failure to establish and/or maintain gamma range oscillations.

Wavelet transform of the EEG reveals differences in low and high gamma responses to elementary visual stimuli.

Multiunit electrophysiological studies indicate that oscillatory activity is common in the awake mammalian central nervous system. Synchronous 20-80 Hz oscillations, so called gamma rhythms, have been proposed as a possible fundamental physiological mechanism of binding neuronal activity underlying object recognition. The purpose of this study was to determine whether or not gamma band oscillatory activity in the human brain is modulated by attributes of elementary visual stimulation. The experiment was performed on 7 normal subjects. Sinusoidal gratings were presented over a range of spatial frequencies. Evoked potentials were recorded over 5 surface electrodes placed in a horizontal occipital chain across the back of the head. Discrete wavelet transform was performed on the first 200 msec following stimulus onset on the average data of 256 sweeps. Power was analyzed with ANOVA across conditions. In our previous studies we have separated a "low" (14-28 Hz) and "high" (28-55 Hz) gamma band. The current results indicate that both gamma bands to full-field stimulation have the highest power at the midline (inion) electrode to a spatial frequency of 5.5 cpd, which is the peak spatial frequency from foveal psychophysical data. However, the spatial frequency bandwidth is considerably narrower in the HG than in the LG band. Occipital spatial frequency tuning of the massed high gamma response is narrower than the tuning of individual cortical neurons. The bandwidth difference between low and high gamma band suggests that different frequency gamma range oscillations may represent not only different functional properties of visual processing, but may also reflect underlying differences in excitatory and postsynaptic inhibitory circuits shaping the contrast sensitivity of the human observer. Our study emphasizes the importance of elementary visual filter properties for gamma responses and the need to subdivide gamma frequency ranges according to functional properties.

Long-Range Cortical Synchronization without Concomitant Oscillations in the Somatosensory System of Anesthetized Cats

To determine whether neuronal oscillations are essential for long-range cortical synchronization in the somatosensory system, we characterized the incidence and response properties of gamma range oscillations (20-80 Hz) among pairs of synchronized neurons in primary (SI) and secondary (SII) somatosensory cortex. Synchronized SI and SII discharges, which occurred within a 3 msec period, were detected in 13% (80 of 621) of single-unit pairs and 25% (29 of 118) of multiunit pairs. Power spectra derived from the auto-correlation histograms (ACGs) revealed that approximately 15% of the neurons forming synchronized pairs were characterized by oscillations. Although 24% of the synchronized neuron pairs (19/80) were characterized by oscillations in one or both neurons, only 1% (1/80) of these pairs displayed oscillations at the same frequency in both neurons. Similar results were observed among pairs of multiunit responses. When single-trial responses were analyzed, the vast majority of responses still did not exhibit oscillations in the gamma frequency range. These results suggest that separate populations of cortical neurons can be bound together without being constrained by the phase relationships defined by specific oscillatory frequencies.

88. Perceptual deficits in schizophrenia may be explained by aberrant gamma range oscillations

Problems in cognition in schizophrenia may be explained by a problem in the timing of neural processes across different cortical regions. We explored a possible connection between backward masking deficits in schizophrenia and aberrant gamma range cortical oscillations. Backward masking is a procedure that assesses the earliest components of visual processing. On this procedure, the visibility of a briefly-presented target is reduced by a visual mask. Schizophrenic patients consistently show deficits on this procedure. As the interval between target and mask increases, backward masking performance sometimes shows an oscillating pattern, which is thought to reflect gamma oscillations of visual pathways. Previously, we found that normal controls showed an oscillating pattern, whereas schizophrenic patients did not show such a pattern. We recently developed a computerized version of backward masking that is well suited for modeling the performance pattern in masking. Intervals between target and mask were set regularly at 13 ms increments, and a threshold procedure was used to equate subjects for initial performance. On this procedure we found the predicted qualitative differences between patients and normal comparison subjects. There was a significant oscillating component for the comparison subjects, (i.e., a sin wave fit the data), but there was no such component for patients. The pattern of results suggest that a fundamental abnormality in establishing cortical oscillations may partially account for backward masking deficits in schizophrenia. It is likely that sensory and perceptual neurocognitive deficits in schizophrenia may have common roots in a failure to establish cortical oscillations.

Gamma-range oscillations in backward-masking functions and their putative neural correlates.

Gamma-range oscillations in backward-masking functions and their putative neural correlates.

Gamma-range oscillations in backward-masking functions and their putative neural correlates.

Backward-masking functions have been hitherto categorized into two types, commonly named Type A and Type B. The analysis of a model of Retino-Cortical Dynamics produces the prediction that spatially localized stimuli should reveal an oscillatory metacontrast function. The predicted new type of metacontrast masking function was investigated in a psychophysical experiment. The results show oscillatory metacontrast functions with significant power in the gamma range (30-70 Hz). A marked decrease in the oscillations is observed when the spatial extent of the stimuli is increased. The theoretical basis of the study relates the oscillations found in the metacontrast function to gamma-range oscillations observed in scalp and intracerebral recordings. The qualitative agreement between the model and data provides support for this putative relationship.