Synchronized Oscillations During Cooperative Feature Linking in a Cortical Model of Visual Perception

A neural network model of synchronized oscillator activity in visual cortex is presented in order to account for recent neurophysiological findings that such synchronization may reflect global properties of the stimulus. In these recent experiments, it was reported that synchronization of oscillatory firing responses to moving bar stimuli occurred not only for nearby neurons, but also occurred between neurons separated by several cortical columns (several mm of cortex) when these neurons shared some receptive field preferences specific to the stimuli. These results were obtained not only for single bar stimuli but also across two disconnected, but colinear, bars moving in the same direction. Our model and computer simulations obtain these synchrony results across both single and double bar stimuli. For the double bar case, synchronous oscillations are induced in the region between the bars, but no oscillations are induced in the regions beyond the stimuli. These results were achieved with cellular units that exhibit limit cycle oscillations for a robust range of input values, but which approach an equilibrium state when undriven. Single and double bar synchronization of these oscillators was achieved by different, but formally related, models of preattentive visual boundary segmentation and attentive visual object recognition, as well as nearest-neighbor and randomly coupled models. In preattentive visual segmentation, synchronous oscillations may reflect the binding of local feature detectors into a globally coherent grouping. In object recognition, synchronous oscillations may occur during an attentive resonant state that triggers new learning. These modelling results support earlier theoretical predictions of synchronous visual cortical oscillations and demonstrate the robustness of the mechanisms capable of generating synchrony.Air Force Office of Scientific Research (90-0175); Army Research Office (DAAL-03-88-K0088); Defense Advanced Research Projects Agency (90-0083); National Aeronautics and Space Administration (NGT-50497

Alpha Oscillations and Early Stages of Visual Encoding

For a long time alpha oscillations have been functionally linked to the processing of visual information. Here we propose an new theory about the functional meaning of alpha. The central idea is that synchronized alpha reflects a basic processing mode that controls access to information stored in a complex long-term memory system, which we term knowledge system in order to emphasize that it comprises not only declarative memories but any kind of knowledge comprising also procedural information. Based on this theoretical background, we assume that during early stages of perception, alpha “directs the flow of information” to those neural structures which represent information that is relevant for encoding. The physiological function of alpha is interpreted in terms of inhibition. We assume that alpha enables access to stored information by inhibiting task-irrelevant neuronal structures and by timing cortical activity in task relevant neuronal structures. We discuss a variety findings showing that evoked alpha and phase locking reflect successful encoding of global stimulus features in an early post-stimulus interval of about 0–150 ms

High-frequency neural oscillations and visual processing deficits in schizophrenia

Visual information is fundamental to how we understand our environment, make predictions, and interact with others. Recent research has underscored the importance of visuo-perceptual dysfunctions for cognitive deficits and pathophysiological processes in schizophrenia. In the current paper, we review evidence for the relevance of high frequency (beta/gamma) oscillations towards visuo-perceptual dysfunctions in schizophrenia. In the first part of the paper, we examine the relationship between beta/gamma band oscillations and visual processing during normal brain functioning. We then summarize EEG/MEG-studies which demonstrate reduced amplitude and synchrony of high-frequency activity during visual stimulation in schizophrenia. In the final part of the paper, we identify neurobiological correlates as well as offer perspectives for future research to stimulate further inquiry into the role of high-frequency oscillations in visual processing impairments in the disorder

Dissipation and spontaneous symmetry breaking in brain dynamics

We compare the predictions of the dissipative quantum model of brain with neurophysiological data collected from electroencephalograms resulting from high-density arrays fixed on the surfaces of primary sensory and limbic areas of trained rabbits and cats. Functional brain imaging in relation to behavior reveals the formation of coherent domains of synchronized neuronal oscillatory activity and phase transitions predicted by the dissipative model.Comment: Restyled, slight changes in title and abstract, updated bibliography, J. Phys. A: Math. Theor. Vol. 41 (2008) in prin

Targeting mGlu5 metabotropic glutamate receptors in the treatment of cognitive dysfunction in a mouse model of phenylketonuria

We studied group-I metabotropic glutamate (mGlu) receptors in Pah(enu2) (ENU2) mice, which mimic the genetics and neurobiology of human phenylketonuria (PKU), a metabolic disorder characterized, if untreated, by autism, and intellectual disability (ID). Male ENU2 mice showed increased mGlu5 receptor protein levels in the hippocampus and corpus striatum (but not in the prefrontal cortex) whereas the transcript of the mGlu5 receptor was unchanged. No changes in mGlu1 receptor mRNA and protein levels were found in any of the three brain regions of ENU2 mice. We extended the analysis to Homer proteins, which act as scaffolds by linking mGlu1 and mGlu5 receptors to effector proteins. Expression of the long isoforms of Homer was significantly reduced in the hippocampus of ENU2 mice, whereas levels of the short Homer isoform (Homer 1a) were unchanged. mGlu5 receptors were less associated to immunoprecipitated Homer in the hippocampus of ENU2 mice. The lack of mGlu5 receptor-mediated long-term depression (LTD) in wild-type mice (of BTBR strain) precluded the analysis of hippocampal synaptic plasticity in ENU2 mice. We therefore performed a behavioral analysis to examine whether pharmacological blockade of mGlu5 receptors could correct behavioral abnormalities in ENU2 mice. Using the same apparatus we sequentially assessed locomotor activity, object exploration, and spatial object recognition (spatial novelty test) after displacing some of the objects from their original position in the arena. Systemic treatment with the mGlu5 receptor antagonist, MPEP (20 mg/kg, i.p.), had a striking effect in the spatial novelty test by substantially increasing the time spent in exploring the displaced objects in ENU2 mice (but not in wild-type mice). These suggest a role for mGlu5 receptors in the pathophysiology of ID in PKU and suggest that, also in adult untreated animals, cognitive dysfunction may be improved by targeting these receptors with an appropriate therapy

Irregular speech rate dissociates auditory cortical entrainment, evoked responses, and frontal alpha

The entrainment of slow rhythmic auditory cortical activity to the temporal regularities in speech is considered to be a central mechanism underlying auditory perception. Previous work has shown that entrainment is reduced when the quality of the acoustic input is degraded, but has also linked rhythmic activity at similar time scales to the encoding of temporal expectations. To understand these bottom-up and top-down contributions to rhythmic entrainment, we manipulated the temporal predictive structure of speech by parametrically altering the distribution of pauses between syllables or words, thereby rendering the local speech rate irregular while preserving intelligibility and the envelope fluctuations of the acoustic signal. Recording EEG activity in human participants, we found that this manipulation did not alter neural processes reflecting the encoding of individual sound transients, such as evoked potentials. However, the manipulation significantly reduced the fidelity of auditory delta (but not theta) band entrainment to the speech envelope. It also reduced left frontal alpha power and this alpha reduction was predictive of the reduced delta entrainment across participants. Our results show that rhythmic auditory entrainment in delta and theta bands reflect functionally distinct processes. Furthermore, they reveal that delta entrainment is under top-down control and likely reflects prefrontal processes that are sensitive to acoustical regularities rather than the bottom-up encoding of acoustic features

The spectro-contextual encoding and retrieval theory of episodic memory.

The spectral fingerprint hypothesis, which posits that different frequencies of oscillations underlie different cognitive operations, provides one account for how interactions between brain regions support perceptual and attentive processes (Siegel etal., 2012). Here, we explore and extend this idea to the domain of human episodic memory encoding and retrieval. Incorporating findings from the synaptic to cognitive levels of organization, we argue that spectrally precise cross-frequency coupling and phase-synchronization promote the formation of hippocampal-neocortical cell assemblies that form the basis for episodic memory. We suggest that both cell assembly firing patterns as well as the global pattern of brain oscillatory activity within hippocampal-neocortical networks represents the contents of a particular memory. Drawing upon the ideas of context reinstatement and multiple trace theory, we argue that memory retrieval is driven by internal and/or external factors which recreate these frequency-specific oscillatory patterns which occur during episodic encoding. These ideas are synthesized into a novel model of episodic memory (the spectro-contextual encoding and retrieval theory, or "SCERT") that provides several testable predictions for future research

Neural population coding: combining insights from microscopic and mass signals

Behavior relies on the distributed and coordinated activity of neural populations. Population activity can be measured using multi-neuron recordings and neuroimaging. Neural recordings reveal how the heterogeneity, sparseness, timing, and correlation of population activity shape information processing in local networks, whereas neuroimaging shows how long-range coupling and brain states impact on local activity and perception. To obtain an integrated perspective on neural information processing we need to combine knowledge from both levels of investigation. We review recent progress of how neural recordings, neuroimaging, and computational approaches begin to elucidate how interactions between local neural population activity and large-scale dynamics shape the structure and coding capacity of local information representations, make them state-dependent, and control distributed populations that collectively shape behavior