MEG-measured visually induced gamma-band oscillations in chronic schizophrenia: Evidence for impaired generation of rhythmic activity in ventral stream regions

Background: Gamma-band oscillations are prominently impaired in schizophrenia, but the nature of the deficit and relationship to perceptual processes is unclear. Methods: 16 patients with chronic schizophrenia (ScZ) and 16 age-matched healthy controls completed a visual paradigm while magnetoencephalographic (MEG) data was recorded. Participants had to detect randomly occurring stimulus acceleration while viewing a concentric moving grating. MEG data were analyzed for spectral power (1-100 Hz) at sensorand source-level to examine the brain regions involved in aberrant rhythmic activity, and for contribution of differences in baseline activity towards the generation of low- and highfrequency power. Results: Our data show reduced gamma-band power at sensor level in schizophrenia patients during stimulus processing while alpha-band and baseline spectrum were intact. Differences in oscillatory activity correlated with reduced behavioral detection rates in the schizophrenia group and higher scores on the “Cognitive Factor” of the Positive and Negative Syndrome Scale. Source reconstruction revealed that extra-striate (fusiform/lingual gyrus), but not striate (cuneus), visual cortices contributed towards the reduced activity observed at sensorlevel in ScZ patients. Importantly, differences in stimulus-related activity were not due to differences in baseline activity. Conclusions: Our findings highlight that MEG-measured high-frequency oscillations during visual processing can be robustly identified in ScZ. Our data further suggest impairments that involve dysfunctions in ventral stream processing and a failure to increase gamma-band activity in a task-context. Implications of these findings are discussed in the context of current theories of cortical-subcortical circuit dysfunctions and perceptual processing in ScZ

No changes in parieto-occipital alpha during neural phase locking to visual quasi-periodic theta-, alpha-, and beta-band stimulation

Recent studies have probed the role of the parieto‐occipital alpha rhythm (8 – 12 Hz) in human visual perception through attempts to drive its neural generators. To that end, paradigms have used high‐intensity strictly‐periodic visual stimulation that created strong predictions about future stimulus occurrences and repeatedly demonstrated perceptual consequences in line with an entrainment of parieto‐occipital alpha. Our study, in turn, examined the case of alpha entrainment by non‐predictive low‐intensity quasi‐periodic visual stimulation within theta‐ (4 – 7 Hz), alpha‐ (8 – 13 Hz) and beta (14 – 20 Hz) frequency bands, i.e. a class of stimuli that resemble the temporal characteristics of naturally occurring visual input more closely. We have previously reported substantial neural phase‐locking in EEG recording during all three stimulation conditions. Here, we studied to what extent this phase‐locking reflected an entrainment of intrinsic alpha rhythms in the same dataset. Specifically, we tested whether quasi‐periodic visual stimulation affected several properties of parieto‐occipital alpha generators. Speaking against an entrainment of intrinsic alpha rhythms by non‐predictive low‐intensity quasi‐periodic visual stimulation, we found none of these properties to show differences between stimulation frequency bands. In particular, alpha band generators did not show increased sensitivity to alpha band stimulation and Bayesian inference corroborated evidence against an influence of stimulation frequency. Our results set boundary conditions for when and how to expect effects of entrainment of alpha generators and suggest that the parieto‐occipital alpha rhythm may be more inert to external influences than previously thought

Order-Based Representation in Random Networks of Cortical Neurons

The wide range of time scales involved in neural excitability and synaptic transmission might lead to ongoing change in the temporal structure of responses to recurring stimulus presentations on a trial-to-trial basis. This is probably the most severe biophysical constraint on putative time-based primitives of stimulus representation in neuronal networks. Here we show that in spontaneously developing large-scale random networks of cortical neurons in vitro the order in which neurons are recruited following each stimulus is a naturally emerging representation primitive that is invariant to significant temporal changes in spike times. With a relatively small number of randomly sampled neurons, the information about stimulus position is fully retrievable from the recruitment order. The effective connectivity that makes order-based representation invariant to time warping is characterized by the existence of stations through which activity is required to pass in order to propagate further into the network. This study uncovers a simple invariant in a noisy biological network in vitro; its applicability under in vivo constraints remains to be seen

Dynamic excitatory and inhibitory gain modulation can produce flexible, robust and optimal decision-making

<div><p>Behavioural and neurophysiological studies in primates have increasingly shown the involvement of urgency signals during the temporal integration of sensory evidence in perceptual decision-making. Neuronal correlates of such signals have been found in the parietal cortex, and in separate studies, demonstrated attention-induced gain modulation of both excitatory and inhibitory neurons. Although previous computational models of decision-making have incorporated gain modulation, their abstract forms do not permit an understanding of the contribution of inhibitory gain modulation. Thus, the effects of co-modulating both excitatory and inhibitory neuronal gains on decision-making dynamics and behavioural performance remain unclear. In this work, we incorporate time-dependent co-modulation of the gains of both excitatory and inhibitory neurons into our previous biologically based decision circuit model. We base our computational study in the context of two classic motion-discrimination tasks performed in animals. Our model shows that by simultaneously increasing the gains of both excitatory and inhibitory neurons, a variety of the observed dynamic neuronal firing activities can be replicated. In particular, the model can exhibit winner-take-all decision-making behaviour with higher firing rates and within a significantly more robust model parameter range. It also exhibits short-tailed reaction time distributions even when operating near a dynamical bifurcation point. The model further shows that neuronal gain modulation can compensate for weaker recurrent excitation in a decision neural circuit, and support decision formation and storage. Higher neuronal gain is also suggested in the more cognitively demanding reaction time than in the fixed delay version of the task. Using the exact temporal delays from the animal experiments, fast recruitment of gain co-modulation is shown to maximize reward rate, with a timescale that is surprisingly near the experimentally fitted value. Our work provides insights into the simultaneous and rapid modulation of excitatory and inhibitory neuronal gains, which enables flexible, robust, and optimal decision-making.</p></div

Interpreting EEG alpha activity

Exploring EEG alpha oscillations has generated considerable interest, in particular with regards to the role they play in cognitive, psychomotor, psycho-emotional and physiological aspects of human life. However, there is no clearly agreed upon definition of what constitutes ‘alpha activity’ or which of the many indices should be used to characterize it. To address these issues this review attempts to delineate EEG alpha-activity, its physical, molecular and morphological nature, and examine the following indices: (1) the individual alpha peak frequency; (2) activation magnitude, as measured by alpha amplitude suppression across the individual alpha bandwidth in response to eyes opening, and (3) alpha “auto-rhythmicity” indices: which include intra-spindle amplitude variability, spindle length and steepness. Throughout, the article offers a number of suggestions regarding the mechanism(s) of alpha activity related to inter and intra-individual variability. In addition, it provides some insights into the various psychophysiological indices of alpha activity and highlights their role in optimal functioning and behavior

The Brain's Router: A Cortical Network Model of Serial Processing in the Primate Brain

The human brain efficiently solves certain operations such as object recognition and categorization through a massively parallel network of dedicated processors. However, human cognition also relies on the ability to perform an arbitrarily large set of tasks by flexibly recombining different processors into a novel chain. This flexibility comes at the cost of a severe slowing down and a seriality of operations (100–500 ms per step). A limit on parallel processing is demonstrated in experimental setups such as the psychological refractory period (PRP) and the attentional blink (AB) in which the processing of an element either significantly delays (PRP) or impedes conscious access (AB) of a second, rapidly presented element. Here we present a spiking-neuron implementation of a cognitive architecture where a large number of local parallel processors assemble together to produce goal-driven behavior. The precise mapping of incoming sensory stimuli onto motor representations relies on a “router” network capable of flexibly interconnecting processors and rapidly changing its configuration from one task to another. Simulations show that, when presented with dual-task stimuli, the network exhibits parallel processing at peripheral sensory levels, a memory buffer capable of keeping the result of sensory processing on hold, and a slow serial performance at the router stage, resulting in a performance bottleneck. The network captures the detailed dynamics of human behavior during dual-task-performance, including both mean RTs and RT distributions, and establishes concrete predictions on neuronal dynamics during dual-task experiments in humans and non-human primates

Lamina-specific cortical dynamics in human visual and sensorimotor cortices

10.7554/eLife.33977.001Distinct anatomical and spectral channels are thought to play specialized roles in the communication within cortical networks. While activity in the alpha and beta frequency range (7 – 40 Hz) is thought to predominantly originate from infragranular cortical layers conveying feedback-related information, activity in the gamma range (>40 Hz) dominates in supragranular layers communicating feedforward signals. We leveraged high precision MEG to test this proposal, directly and non-invasively, in human participants performing visually cued actions. We found that visual alpha mapped onto deep cortical laminae, whereas visual gamma predominantly occurred more superficially. This lamina-specificity was echoed in movement-related sensorimotor beta and gamma activity. These lamina-specific pre- and post- movement changes in sensorimotor beta and gamma activity suggest a more complex functional role than the proposed feedback and feedforward communication in sensory cortex. Distinct frequency channels thus operate in a lamina-specific manner across cortex, but may fulfill distinct functional roles in sensory and motor processes