On the emergence of cognition: from catalytic closure to neuroglial closure.

In an analogous manner as occurred during the development of a connected metabolism that at some point reached characteristics associated with what is called "life"-due mainly to a catalytic closure phenomenon when chemicals started to autocatalyze themselves forming a closed web of chemical reactions-it is here proposed that cognition and consciousness (or features associated with them) arose as a consequence of another type of closure within the nervous system, the brain especially. Proper brain function requires an efficient web of connections and once certain complexity is attained due to the number and coordinated activities of the brain cell networks, the emergent properties of cognition and consciousness take place. Seeking to identify main features of the nervous system organization for optimal function, it is here proposed that while catalytic closure yielded life, neuroglial closure produced cognition/consciousness.

Author Correction: Exploring the alpha desynchronization hypothesis in resting state networks with intracranial electroencephalography and wiring cost estimates.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.

Closed-Loop Neurostimulators: A Survey and A Seizure-Predicting Design Example for Intractable Epilepsy Treatment.

First, existing commercially available open-loop and closed-loop implantable neurostimulators are reviewed and compared in terms of their targeted application, physical size, system-level features, and performance as a medical device. Next, signal processing algorithms as the primary strength point of the closed-loop neurostimulators are reviewed, and various design and implementation requirements and trade-offs are discussed in details along with quantitative examples. The review results in a set of guidelines for algorithm selection and evaluation. Second, the implementation of an inductively-powered seizure-predicting microsystem for monitoring and treatment of intractable epilepsy is presented. The miniaturized system is comprised of two miniboards and a power receiver coil. The first board hosts a 24-channel neurostimulator system on chip fabricated in a [Formula: see text] CMOS technology and performs neural recording, on-chip digital signal processing, and electrical stimulation. The second board communicates recorded brain signals as well as signal processing results wirelessly. The multilayer flexible coil receives inductively-transmitted power. The system is sized at 2 × 2 × 0.7 [Formula: see text] and weighs 6 g. The approach is validated in the control of chronic seizures in vivo in freely moving rats.

320-channel active probe for high-resolution neuromonitoring and responsive neurostimulation.

We present a 320-channel active probe for high-spatial-resolution neuromonitoring and responsive neurostimulation. The probe comprises an integrated circuit (IC) cell array bonded to the back side of a pitch-matched microelectrode array. The IC enables up to 256-site neural recording and 64-site neural stimulation at the spatial resolution of 400 µ m and 200 µ m, respectively. It is suitable for direct integration with electrode arrays with the shank pitch of integer multiples of 200 µm. In the presented configuration, the IC is bonded with a 8 × 8 400 µ m-pitch Utah electrode array (UEA) and up to additional 192 recording channels are used for peripheral neuromonitoring. The 0.35 µ m CMOS circuit array has a total die size of 3.5 mm × 3.65 mm. Each stimulator channel employs a current memory for simultaneous multi-site neurostimulation, outputs 20 µA-250 µA square or arbitrary waveform current, occupies 0.02 mm (2), and dissipates 2.76 µ W quiescent power. Each fully differential recording channel has two stages of amplification and filtering and an 8-bit single-slope ADC, occupies 0.035 mm (2) , and consumes 51.9 µ W. The neural probe has been experimentally validated in epileptic seizure propagation studies in a mouse hippocampal slice in vitro and in responsive neurostimulation for seizure suppression in an acute epilepsy rat model in vivo .

Power law scaling in synchronization of brain signals depends on cognitive load.

As it has several features that optimize information processing, it has been proposed that criticality governs the dynamics of nervous system activity. Indications of such dynamics have been reported for a variety of in vitro and in vivo recordings, ranging from in vitro slice electrophysiology to human functional magnetic resonance imaging. However, there still remains considerable debate as to whether the brain actually operates close to criticality or in another governing state such as stochastic or oscillatory dynamics. A tool used to investigate the criticality of nervous system data is the inspection of power-law distributions. Although the findings are controversial, such power-law scaling has been found in different types of recordings. Here, we studied whether there is a power law scaling in the distribution of the phase synchronization derived from magnetoencephalographic recordings during executive function tasks performed by children with and without autism. Characterizing the brain dynamics that is different between autistic and non-autistic individuals is important in order to find differences that could either aid diagnosis or provide insights as to possible therapeutic interventions in autism. We report in this study that power law scaling in the distributions of a phase synchrony index is not very common and its frequency of occurrence is similar in the control and the autism group. In addition, power law scaling tends to diminish with increased cognitive load (difficulty or engagement in the task). There were indications of changes in the probability distribution functions for the phase synchrony that were associated with a transition from power law scaling to lack of power law (or vice versa), which suggests the presence of phenomenological bifurcations in brain dynamics associated with cognitive load. Hence, brain dynamics may fluctuate between criticality and other regimes depending upon context and behaviors.

A model of functional brain connectivity and background noise as a biomarker for cognitive phenotypes: application to autism.

We present an efficient approach to discriminate between typical and atypical brains from macroscopic neural dynamics recorded as magnetoencephalograms (MEG). Our approach is based on the fact that spontaneous brain activity can be accurately described with stochastic dynamics, as a multivariate Ornstein-Uhlenbeck process (mOUP). By fitting the data to a mOUP we obtain: 1) the functional connectivity matrix, corresponding to the drift operator, and 2) the traces of background stochastic activity (noise) driving the brain. We applied this method to investigate functional connectivity and background noise in juvenile patients (n = 9) with Asperger's syndrome, a form of autism spectrum disorder (ASD), and compared them to age-matched juvenile control subjects (n = 10). Our analysis reveals significant alterations in both functional brain connectivity and background noise in ASD patients. The dominant connectivity change in ASD relative to control shows enhanced functional excitation from occipital to frontal areas along a parasagittal axis. Background noise in ASD patients is spatially correlated over wide areas, as opposed to control, where areas driven by correlated noise form smaller patches. An analysis of the spatial complexity reveals that it is significantly lower in ASD subjects. Although the detailed physiological mechanisms underlying these alterations cannot be determined from macroscopic brain recordings, we speculate that enhanced occipital-frontal excitation may result from changes in white matter density in ASD, as suggested in previous studies. We also venture that long-range spatial correlations in the background noise may result from less specificity (or more promiscuity) of thalamo-cortical projections. All the calculations involved in our analysis are highly efficient and outperform other algorithms to discriminate typical and atypical brains with a comparable level of accuracy. Altogether our results demonstrate a promising potential of our approach as an efficient biomarker for altered brain dynamics associated with a cognitive phenotype.

Experimental observation of increased fluctuations in an order parameter before epochs of extended brain synchronization.

The identification of epileptic seizure precursors has potential clinical relevance. It is conjectured that seizures may be represented by dynamical bifurcations and that an adequate order parameter to characterize brain dynamics is the phase difference in the oscillatory activity of neural systems. In this study, the critical point hypothesis that seizures, or more generally periods of widespread high synchronization, represent bifurcations is empirically tested by monitoring the growth of fluctuations in the putative order parameter of phase differences between magnetoencephalographic and electroencephalographic signals in nearby brain regions in patients with epilepsy and normal subjects during hyperventilation. Implications of the results with regard to epileptic phenomena are discussed.

The circuitry of atypical absence seizures in GABA(B)R1a transgenic mice.

The objective of the current study was to determine the origin of the slow spike and wave discharges (SSWD) in the transgenic mouse with postnatal over-expression of the GABA(B) receptor subunit R1a (GABA(B)R1a(tg)), a mutant animal with a characteristic phenotype consisting of atypical absence seizures and cognitive dysfunction. Using simultaneous electrocorticographic (ECoG) recordings from cortical and depth electrodes in freely moving GABA(B)R1a(tg) mice, we showed that the SSWD in this model of atypical absence seizures arise exclusively from midline thalamus (MT), reticular nucleus of the thalamus (nRT), and the CA1 region of the hippocampus. Lesioning of the MT and nRT with ibotenic acid abolished SSWD. Microinjection of the GABA(B) receptor agonist, (-) baclofen, into MT and nRT exacerbated, and the GABA(B)R antagonist, CGP 35348 abolished, SSWD in the GABA(B)R1a(tg) mice. These data suggest that the nRT and MT are necessary for the generation of SSWD in the GABA(B)R1a(tg) model of atypical absence seizures, and indicate that GABA(B)R-mediated mechanisms within thalamus are necessary for the genesis of SSWD in atypical absence seizures. A putative cortico-thalamo-hippocampal circuit is proposed to explain the unique electrographic findings, ictal behavior, pharmacology, and impairment of cognition that characterize atypical absence seizures.

The sign of the cross as a learned ictal automatism?

Described here is a case of a patient who made the sign of the cross during right mesial temporal seizures, documented by intracranial depth electrode and simultaneous scalp video-EEG. The patient was ultimately found to have predominantly left temporal lobe epilepsy, and she was rendered seizure free for many years following a left anterior temporal lobe resection. Most interestingly, however, was a suggestion that in her case, making the sign of the cross may have represented a learned ictal behavioral phenomenon: the patient had been forced, over a period of many years, to make this gesture as an atonement in the postictal period. The movement ultimately came to be performed unconsciously, during the ictus, associated with a lateralized seizure discharge in the right temporal lobe. In contrast to seizure-induced experiential phenomena and typical motor automatisms, where the behavioral manifestations have no recognized association with learning, we wondered whether the pathophysiological mechanisms of chronic focal epilepsy had subserved in this case a psychological learning process, whereby right temporal seizures were ultimately able to recruit and activate an adjacent neural memory circuit.

The effects of a ketogenic diet on ATP concentrations and the number of hippocampal mitochondria in Aldh5a1(-/-) mice.

BACKGROUND: Succinic semialdehyde dehydrogenase (SSADH) deficiency is an inborn error of GABA metabolism characterized clinically by ataxia, psychomotor retardation and seizures. A mouse model of SSADH deficiency, the Aldh5a1(-/-) mouse, has been used to study the pathophysiology and treatment of this disorder. Recent work from our group has shown that the ketogenic diet (KD) is effective in normalizing the Aldh5a1(-/-) phenotype, although the mechanism of the effect remains unclear. METHODS: Here, we examine the effects of a KD on the number of hippocampal mitochondria as well as on ATP levels in hippocampus. Electron microscopy was performed to determine the number of mitochondria in the hippocampus of Aldh5a1(-/-) mice. Adenosine triphosphate (ATP) levels were measured in hippocampal extracts. RESULTS: Our results show that the KD increases the number of mitochondria in Aldh5a1(-/-) mice. We also show that Aldh5a1(-/-) mice have significant reductions in hippocampal ATP levels as compared to controls, and that the KD restores ATP in mutant mice to normal levels. GENERAL SIGNIFICANCE: Taken together, our data suggest that the KD's actions on brain mitochondria may play a role in the diet's ability to treat murine SSADH deficiency.

A ketogenic diet rescues the murine succinic semialdehyde dehydrogenase deficient phenotype.

Succinic semialdehyde dehydrogenase (SSADH) deficiency is a heritable disorder of GABA degradation characterized by ataxia, psychomotor retardation and seizures. To date, there is no effective treatment for SSADH deficiency. We tested the hypothesis that a ketogenic diet (KD) would improve outcome in an animal model of SSADH deficiency, the SSADH knockout mouse (Aldh5a1-/-). Using a 4:1 ratio of fat to combined carbohydrate and protein KD we set out to compare the general phenotype, in vivo and in vitro electrophysiology and [35S]TBPS binding in both Aldh5a1-/- mice and control (Aldh5a1+/+) mice. We found that the KD prolonged the lifespan of mutant mice by >300% with normalization of ataxia, weight gain and EEG compared to mutants fed a control diet. Aldh5a1-/- mice showed significantly reduced mIPSC frequency in CA1 hippocampal neurons as well as significantly decreased [35S]TBPS binding in all brain areas examined. In KD fed mutants, mIPSC activity normalized and [35S]TBPS binding was restored in the cortex and hippocampus. The KD appears to reverse toward normal the perturbations seen in Aldh5a1-/- mice. Our data suggest that the KD may work in this model by restoring GABAergic inhibition. These data demonstrate a successful experimental treatment for murine SSADH deficiency using a KD, giving promise to the idea that the KD may be successful in the clinical treatment of SSADH deficiency.

Fluctuations in neuronal synchronization in brain activity correlate with the subjective experience of visual recognition.

The scientific study of subjective experience is a current major research area in the neurosciences. Coordination patterns of brain activity are being studied to address the question of how brain function relates to behaviour, and particularly methods to estimate neuronal synchronization can unravel the spatio-temporal dynamics of the transient formation of neuronal assemblies. We report here a biophysical correlate of subjective experience. Subjects visualised figures with different levels of noise, while their brain activity was recorded using magnetoencephalography (MEG), and reported the moment in time (corresponding to a noise level) of figure recognition, which varied between individuals, as well as the moment when they saw the figure more clearly, which was mostly common among the participants (thus less subjective). This latter moment is considered to represent psychophysical stochastic resonance (PSR). Fluctuations in neuronal synchronization, quantified using a diffusion coefficient, were lower in occipital cortex when subjects recognised the figure, for a certain noise level, but did not correlate with the moment of PSR. A different pattern was observed in frontal cortex, where lower values of the diffusion coefficient in neuronal synchronization was maintained from the moment of recognition to the moment of PSR. No specific pattern was found analysing signals from temporal or parietal cortical areas. These observations provide support for distinct synchronization patterns in different cortical areas, and represent another demonstration that the subjective, first-person perspective is accessible to scientific methods.

Phase synchronization measurements using electroencephalographic recordings: what can we really say about neuronal synchrony?

Phase synchrony analysis is a relatively new concept that is being increasingly used on neurophysiological data obtained through different methodologies. It is currently believed that phase synchrony is an important signature of information binding between distant sites of the brain, especially during cognitive tasks. Electroencephalographic (EEG) recordings are the most widely used recording technique for recording brain signals and assessing phase synchrony patterns. In this study, we address the suitability of phase synchrony analysis in EEG recordings. Using geometrical arguments and numerical examples, employing EEG and magnetoencephalographic data, we show that the presence of a common reference signal in the case of EEG recordings results in a distortion of the synchrony values observed, in that the amplitudes of the signals influence the synchrony measured, and in general destroys the intended physical interpretation of phase synchrony.