Is the tendency to maximise energy distribution an optimal collective activity for biological purposes? A proposal for a global principle of biological organization.

Our purpose is to address the biological problem of finding foundations of the organization in the collective activity among cell networks in the nervous system, at the meso/macroscale, giving rise to cognition and consciousness. But in doing so, we encounter another problem related to the interpretation of methods to assess the neural interactions and organization of the neurodynamics, because thermodynamic notions, which have precise meaning only under specific conditions, have been widely employed in these studies. The consequence is that apparently contradictory results appear in the literature, but these contradictions diminish upon the considerations of the specific circumstances of each experiment. After clarifying some of these controversial points and surveying some experimental results, we propose that a necessary condition for cognition/consciousness to emerge is to have available enough energy, or cellular activity; and a sufficient condition is the multiplicity of configurations in which cell networks can communicate, resulting in non-uniform energy distribution, the generation and dissipation of energy gradients due to the constant activity. The diversity of sensorimotor processing of higher animals needs a flexible, fluctuating web on neuronal connections, and we review results supporting such multiplicity of configurations among brain regions associated with conscious awareness and healthy brain states. These ideas may reveal possible fundamental principles of brain organization that could be extended to other natural phenomena and how healthy activity may derive to pathological states.

Consciousness as an Emergent Phenomenon: A Tale of Different Levels of Description.

One of the biggest queries in cognitive sciences is the emergence of consciousness from matter. Modern neurobiological theories of consciousness propose that conscious experience is the result of interactions between large-scale neuronal networks in the brain, traditionally described within the realm of classical physics. Here, we propose a generalized connectionist framework in which the emergence of "conscious networks" is not exclusive of large brain areas, but can be identified in subcellular networks exhibiting nontrivial quantum phenomena. The essential feature of such networks is the existence of strong correlations in the system (classical or quantum coherence) and the presence of an optimal point at which the system's complexity and energy dissipation are maximized, whereas free-energy is minimized. This is expressed either by maximization of the information content in large scale functional networks or by achieving optimal efficiency through the quantum Goldilock effect.

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

This paper addresses a fundamental question, are eyes closed and eyes open resting states equivalent baseline conditions, or do they have consistently different electrophysiological signatures? We compare the functional connectivity patterns in an eyes closed resting state with an eyes open resting state to investigate the alpha desynchronization hypothesis. The change in functional connectivity from eyes closed to eyes open, is here, for the first time, studied with intracranial recordings. We perform network connectivity analysis in iEEG and we find that phase-based connectivity is sensitive to the transition from eyes closed to eyes open only in interhemispheral and frontal electrodes. Power based connectivity, on the other hand, consistently discriminates between the two conditions in temporal and interhemispheral electrodes. Additionally, we provide a calculation for the wiring cost, defined in terms of the connectivity between electrodes weighted by distance. We find that the wiring cost variation from eyes closed to eyes open is sensitive to the eyes closed and eyes open conditions. We extend the standard network-based approach using the filtration method from algebraic topology which does not rely on the threshold selection problem. Both the wiring cost measure defined here and this novel methodology provide a new avenue for understanding the electrophysiology of resting state.

Low-Frequency Noise and Offset Rejection in DC-Coupled Neural Amplifiers: A Review and Digitally-Assisted Design Tutorial.

We review integrated circuits for low-frequency noise and offset rejection as a motivation for the presented digitally-assisted neural amplifier design methodology. Conventional AC-coupled neural amplifiers inherently reject input DC offset but have key limitations in area, linearity, DC drift, and spectral accuracy. Their chopper stabilization reduces low-frequency intrinsic noise at the cost of degraded area, input impedance and design complexity. DC-coupled implementations with digital high-pass filtering yield improved area, linearity, drift, and spectral accuracy and are inherently suitable for simple chopper stabilization. As a design example, a 56-channel 0.13 [Formula: see text] CMOS intracranial EEG interface is presented. DC offset of up to ±50 mV is rejected by a digital low-pass filter and a 16-bit delta-sigma DAC feeding back into the folding node of a folded-cascode LNA with CMRR of 65 dB. A bank of seven column-parallel fully differential SAR ADCs with ENOB of 6.6 are shared among 56 channels resulting in 0.018 [Formula: see text] effective channel area. Compensation-free direct input chopping yields integrated input-referred noise of 4.2 µVrms over the bandwidth of 1 Hz to 1 kHz. The 8.7 [Formula: see text] chip dissipating 1.07 mW has been validated in vivo in online intracranial EEG monitoring in freely moving rats.

Low-Radiation Cellular Inductive Powering of Rodent Wireless Brain Interfaces: Methodology and Design Guide.

This paper presents a general methodology of inductive power delivery in wireless chronic rodent electrophysiology applications. The focus is on such systems design considerations under the following key constraints: maximum power delivery under the allowable specific absorption rate (SAR), low cost and spatial scalability. The methodology includes inductive coil design considerations within a low-frequency ferrite-core-free power transfer link which includes a scalable coil-array power transmitter floor and a single-coil implanted or worn power receiver. A specific design example is presented that includes the concept of low-SAR cellular single-transmitter-coil powering through dynamic tracking of a magnet-less receiver spatial location. The transmitter coil instantaneous supply current is monitored using a small number of low-cost electronic components. A drop in its value indicates the proximity of the receiver due to the reflected impedance of the latter. Only the transmitter coil nearest to the receiver is activated. Operating at the low frequency of 1.5 MHz, the inductive powering floor delivers a maximum of 15.9 W below the IEEE C95 SAR limit, which is over three times greater than that in other recently reported designs. The power transfer efficiency of 39% and 13% at the nominal and maximum distances of 8 cm and 11 cm, respectively, is maintained.

Seizure Suppression Efficacy of Closed-Loop Versus Open-Loop Deep Brain Stimulation in a Rodent Model of Epilepsy.

We assess and compare the effects of both closed-loop and open-loop neurostimulation of the rat hippocampus by means of a custom low-power programmable therapeutic neurostimulation device on the suppression of spontaneous seizures in a rodent model of epilepsy. Chronic seizures were induced by intraperitoneal kainic acid injection. Two bipolar electrodes were implanted into the CA1 regions of both hippocampi. The electrodes were connected to the custom-built programmable therapeutic neurostimulation device that can trigger an electrical stimulation either in a periodic manner or upon detection of the intracerebral electroencephalographic (icEEE) seizure onset. This device includes a microchip consisting of a 256-channel icEEG recording system and a 64-channel stimulator, and a programmable seizure detector implemented in a field-programmable gate array (FPGA). The neurostimulator was used to evaluate seizure suppression efficacy in ten epileptic rats for a total of 240 subject-days (5760 subject-hours). For this purpose, all rats were randomly divided into two groups: the no-stimulation group and the stimulation group. The no-stimulation group did not receive stimulation. The stimulation group received, first, closed-loop stimulation and, next, open-loop stimulation. The no-stimulation and stimulation groups had a similar seizure frequency baseline, averaging five seizures per day. Closed-loop stimulation reduced seizure frequency by 90% and open-loop stimulation reduced seizure frequency by 17%, both in the stimulation group as compared to the no-stimulation group.

Eye movement measurement in diagnostic assessment of disorders of consciousness.

We review the literature to appraise the evidence supporting or disputing the use of eye movement measurement in disorders of consciousness (DOC) with low levels of arousal or awareness, such as minimally conscious state (MCS), vegetative state (VS), and coma for diagnostic and prognostic purposes. We will focus on the effectiveness of each technique in the diagnostic classification of these patients and the gradual trend in research from manual to computerized tracking methods. New tools have become available at clinicians' disposal to assess eye movements with high spatial and temporal fidelity. The close relationship between eye movement generation and organic dysfunction in the brain allows these tools to be applied to the assessment of severe DOC as a unique supplementary toolset. We posit that eye tracking can improve clinical diagnostic precision for DOC, a key component of assessment that often dictates the course of clinical care in DOC patients. We see the emergence of long-term eye-tracking studies with seamless integration of technology in the future to improve the performance of clinical assessment in DOC.

Phase synchronization in electroencephalographic recordings prognosticates outcome in paediatric coma.

Brain injury from trauma, cardiac arrest or stroke is the most important cause of death and acquired disability in the paediatric population. Due to the lifetime impact of brain injury, there is a need for methods to stratify patient risk and ultimately predict outcome. Early prognosis is fundamental to the implementation of interventions to improve recovery, but no clinical model as yet exists. Healthy physiology is associated with a relative high variability of physiologic signals in organ systems. This was first evaluated in heart rate variability research. Brain variability can be quantified through electroencephalographic (EEG) phase synchrony. We hypothesised that variability in brain signals from EEG recordings would correlate with patient outcome after brain injury. Lower variability in EEG phase synchronization, would be associated with poor patient prognosis. A retrospective study, spanning 10 years (2000-2010) analysed the scalp EEGs of children aged 1 month to 17 years in coma (Glasgow Coma Scale, GCS, <8) admitted to the paediatric critical care unit (PCCU) following brain injury from TBI, cardiac arrest or stroke. Phase synchrony of the EEGs was evaluated using the Hilbert transform and the variability of the phase synchrony calculated. Outcome was evaluated using the 6 point Paediatric Performance Category Score (PCPC) based on chart review at the time of hospital discharge. Outcome was dichotomized to good outcome (PCPC score 1 to 3) and poor outcome (PCPC score 4 to 6). Children who had a poor outcome following brain injury secondary to cardiac arrest, TBI or stroke, had a higher magnitude of synchrony (R index), a lower spatial complexity of the synchrony patterns and a lower temporal variability of the synchrony index values at 15 Hz when compared to those patients with a good outcome.

Disrupted cortical conductivity in schizophrenia: TMS-EEG study.

Schizophrenia is conceptualized as a failure of cognitive integration, and altered oscillatory properties of neurocircuits are associated with its symptoms. We hypothesized that abnormal characteristics of neural networks may alter functional connectivity and distort propagation of activation in schizophrenic brains. Thus, electroencephalography (EEG) responses to transcranial magnetic stimulation (TMS) of motor cortex were compared between schizophrenia and healthy subjects. There was no difference in the initial response. However, TMS-induced waves of recurrent excitation spreading across the cortex were observed in schizophrenia, while in healthy subjects the activation faded away soon after stimulation. This widespread activation in schizophrenia was associated with increased oscillatory activities in the proximal central leads and in fronto-temporo-parietal leads bilaterally. A positive correlation was found between increased TMS-induced cortical activation in gamma frequency and positive symptoms of schizophrenia, while negative symptoms were correlated with activation in theta and delta bands. We suggest that excessive activation in response to stimulation in schizophrenia brains may lead to abnormal propagation of the signal that could potentially result in aberrant activity in areas remote from the activation origin. This mechanism may account for the positive symptoms of schizophrenia and could worsen signal to noise deficits, jeopardizing adequate information processing with ensuing cognitive deficits.

The imaginary part of coherency in autism: differences in cortical functional connectivity in preschool children.

Cognition arises from the transient integration and segregation of activity across functionally distinct brain areas. Autism Spectrum Disorders (ASD), which encompass a wide range of developmental disabilities, have been presumed to be associated with a problem in cortical and sub-cortical dynamics of coordinated activity, often involving enhanced local but decreased long range coordination over areas of integration. In this paper we challenge this idea by presenting results from a relatively large population of ASD children and age-matched controls during a face-processing task. Over most of the explored domain, children with ASD exhibited enhanced synchronization, although finer detail reveals specific enhancement/reduction of synchrony depending on time, frequency and brain site. Our results are derived from the use of the imaginary part of coherency, a measure which is not susceptible to volume conduction artifacts and therefore presents a credible picture of coordinated brain activity. We also present evidence that this measure is a good candidate to provide features in building a classifier to be used as a potential biomarker for autism.

Massively-parallel neuromonitoring and neurostimulation rodent headset with nanotextured flexible microelectrodes.

We present a compact wireless headset for simultaneous multi-site neuromonitoring and neurostimulation in the rodent brain. The system comprises flexible-shaft microelectrodes, neural amplifiers, neurostimulators, a digital time-division multiplexer (TDM), a micro-controller and a ZigBee wireless transceiver. The system is built by parallelizing up to four 0.35 µm CMOS integrated circuits (each having 256 neural amplifiers and 64 neurostimulators) to provide a total maximum of 1024 neural amplifiers and 256 neurostimulators. Each bipolar neural amplifier features 54 dB-72 dB adjustable gain, 1 Hz-5 kHz adjustable bandwidth with an input-referred noise of 7.99 µVrms and dissipates 12.9 µW. Each current-mode bipolar neurostimulator generates programmable arbitrary-waveform biphasic current in the range of 20-250 µA and dissipates 2.6 µW in the stand-by mode. Reconfigurability is provided by stacking a set of dedicated mini-PCBs that share a common signaling bus within as small as 22 × 30 × 15 mm³ volume. The system features flexible polyimide-based microelectrode array design that is not brittle and increases pad packing density. Pad nanotexturing by electrodeposition reduces the electrode-tissue interface impedance from an average of 2 MΩ to 30 kΩ at 100 Hz. The rodent headset and the microelectrode array have been experimentally validated in vivo in freely moving rats for two months. We demonstrate 92.8 percent seizure rate reduction by responsive neurostimulation in an acute epilepsy rat model.

Single trial classification of magnetoencephalographic recordings using Granger causality.

The use of Granger causality (GC) for studying dependencies in neuroimaging data has recently been gaining popularity. Several frameworks exist for applying GC to neurophysiological questions but many rely heavily on specific statistical assumptions regarding autoregressive (AR) models for hypothesis testing. Since it is often difficult to satisfy these assumptions in practical settings, this study proposes an alternative statistical methodology based on the classification of individual trials of data. Instead of testing for significance using statistics based on estimated AR models or prediction errors, hypotheses were tested by determining whether or not individual magnetoencephalography (MEG) recording segments belonging to either of two experimental conditions can be successfully classified using features derived from AR and GC concepts. Using this novel approach, we show that bivariate temporal GC can be used to distinguish button presses based on whether they were experimentally forced or free. Additionally, the methodology was used to determine useful parameter settings for various steps of the analysis and this revealed surprising insight into several aspects of AR and GC analysis which, previously, could not be obtained in a comparable manner. A final mean accuracy of 79.2% was achieved for classifying forced and free button presses for 6 subjects suggesting that classification using GC features is a viable option for studying MEG signals and useful for evaluating the effectiveness of parameter variations in GC analysis.

Transient coordinated activity within the developing brain's default network.

The concept of a brain default network postulates that specific brain regions are more active when a person is engaged in introspective mental activity. Transient functional coordination between groups of neurons is thought to be necessary for information processing. Since children develop introspection as they mature, regions of the default network may establish increasing functional coordination with age, resulting in fewer fluctuations in synchronization patterns. We investigated the transient coordinated activity in regions of the default network in seventeen children aged 11 months to 17 years of age using EEG recordings while subjects were resting quietly with eyes closed. The temporal and spatial fluctuations in the phase synchrony patterns were estimated across sites associated with the default network pattern and compared to other regions. Lower variability of the spatio-temporal patterns of phase synchronization associated with the default network was observed in the older group as compared to the younger group. This indicates that functional coordination increases among regions of the default network as children develop.

Fluctuations in cortical synchronization in pediatric traumatic brain injury.

Traumatic brain injury (TBI) is the leading cause of death and acquired disability in the pediatric population worldwide. We hypothesized that electroencephalography (EEG) synchrony and its temporal variability, analyzed during the acute phase following TBI, would be altered from that of normal children and as such would offer insights into TBI pathophysiology. Seventeen pediatric patients with mild to severe head injury admitted to a pediatric critical care unit were recruited along with 10 age- and gender-matched controls. Patients had two electroencephalographs performed 3 days apart. Outcome was measured at 1 year post-TBI utilizing the Pediatric Cerebral Performance Category score (PCPC). Maximal synchrony between EEG channels correlated to areas of primary injury as seen on computed tomography (CT) scan. The temporal variability of phase synchronization among EEG electrodes increased as patients recovered and emerged from coma (p < 0.001). This temporal variability correlated with outcome (Pearson coefficient of 0.74) better than the worst Glasgow Coma Scale score, length of coma, or extent of injury on CT scan. This represents a novel approach in the evaluation of TBI in children.

Enhanced synchrony in epileptiform activity? Local versus distant phase synchronization in generalized seizures.

Synchronization is a fundamental characteristic of complex systems and a basic mechanism of self-organization. A traditional, accepted perspective on epileptiform activity holds that hypersynchrony covering large brain regions is a hallmark of generalized seizures. However, a few recent reports have described substantial fluctuations in synchrony before and during ictal events, thus raising questions as to the widespread synchronization notion. In this study, we used magnetoencephalographic recordings from epileptic patients with generalized seizures and normal control subjects to address the extent of the phase synchronization (phase locking) in local (neighboring) and distant cortical areas and to explore the ongoing temporal dynamics for particular ranges of frequencies at which synchrony occurs, during interictal and ictal activity. Synchronization patterns were found to differ somewhat depending on the epileptic syndrome, with primary generalized absence seizures displaying more long-range synchrony in all frequency bands studied (3-55 Hz) than generalized tonic motor seizures of secondary (symptomatic) generalized epilepsy or frontal lobe epilepsy. However, all seizures were characterized by enhanced local synchrony compared with distant synchrony. There were fluctuations in the synchrony between specific cortical areas that varied from seizure to seizure in the same patient, but in most of the seizures studied, regardless of semiology, there was a constant pattern in the dynamics of synchronization, indicating that seizures proceed by a recruitment of neighboring neuronal networks. Together, these data indicate that the concept of widespread "hypersynchronous" activity during generalized seizures may be misleading and valid only for very specific neuronal ensembles and circumstances.

Changes in neuronal migration in neocortex of connexin43 null mutant mice.

To identify a neural phenotype in connexin43 null mutant mice, electrophysiological properties, intercellular communication and neuronal migration were studied in the developing neocortex. In acute slice preparations from newborn mice, electrophysiological characteristics of cortical and hippocampal neurons were not significantly different between wild type and null mutant mice. However, gap junctional coupling as assessed by fluorescence recovery after photobleaching was significantly attenuated in neocortical brain slices of null mutant mice. To assess neuronal migration, dividing cells were labeled with bromodeoxyuridine (BrdU) on embryonic days 12, 14 and 16, respectively, corresponding to the period of cortical neurogenesis, and the neocortex examined 2 or 3 days after the labeling. BrdU-labeled cells were distributed in the neocortical wall with a significant change in the pattern in the neocortex of the null mutant, where labeled cells accumulated in the intermediate zone or in the inner part of the cortical plate. The result suggests a significant delay in neocortical neuronal migration in the connexin43 null mutants, and a possible role of connexin43 in this process through yet unidentified mechanisms.