Rapid neocortical dynamics: cellular and network mechanisms

Arc regulates experience-dependent persistent firing patterns in frontal cortex

The brain encodes information about past experience in specific populations of neurons that communicate with one another by firing action potentials. Studies of experience-dependent neural plasticity have largely focused on individual synaptic changes in response to neuronal input. Indicative of the neuronal output transmitted to downstream neurons, persistent firing patterns are affected by prior experience in selective neuronal populations. However, little is known about the molecular and cellular mechanisms by which experience-related persistent firing patterns are regulated in specific neuronal populations. Using frontal cortical slices prepared from transgenic mice carrying a fluorescent reporter of Arc gene expression, this study investigates how behavioral experience and the activity-regulated Arc gene affect patterns of neuronal firing. We found that motor training increases Arc expression in subsets of excitatory neurons. Those neurons exhibit persistent firing in contrast to Arc-negative neurons from the same mice or neurons from the untrained mice. Furthermore, in mice carrying genetic deletion of Arc, the frontal cortical circuitry is still in place to initiate experience-dependent gene expression, but the level of persistent firing thereafter is diminished. Finally, our results showed that the emergence of persistent activity is associated with Arc-dependent changes in the function of NMDA-type glutamate receptors, rather than changes in AMPA-type receptors or membrane excitability. Our findings therefore reveal an Arc-dependent molecular pathway by which gene-experience interaction regulates the emergence of persistent firing patterns in specific neuronal populations.

Rapid developmental emergence of stable depolarization during wakefulness by inhibitory balancing of cortical network excitability

The ability to generate behaviorally appropriate cortical network states is central to sensory perception and plasticity, but little is known about the timing and mechanisms of their development. I paired intracellular and extracellular recordings in the visual cortex of awake infant rats to determine the synaptic and circuit mechanisms regulating the development of a key network state, the persistent and stable subthreshold membrane potential (Vm) depolarization associated with wakefulness/alertness in cortical networks, called the "desynchronized" or "activated" state. Current-clamp recordings reveal that the desynchronized state is absent during the first 2 postnatal weeks, despite behavioral wakefulness. During this period, Vm remains at the resting membrane potential >80% of the time, regardless of behavioral state. Vm dynamics during spontaneous or light-evoked activity were highly variable, contained long-duration supratheshold plateau potentials, and high spike probability, suggesting an unstable and hyperexcitable early cortical network. Voltage-clamp recordings reveal that effective feedforward inhibition is absent at these early ages despite the presence of feedback inhibition. Stable membrane depolarization during wakefulness finally emerges 1-2 d before eye opening and is statistically indistinguishable from that in adults within days. Reduced cortical excitability, fast feedforward inhibition, and the slow cortical oscillation appear simultaneously with stable depolarization, suggesting that an absence of inhibitory balance during early development prevents the expression of the active state and hence a normal wakeful state in early cortex. These observations identify feedforward inhibition as a potential key regulator of cortical network activity development.

Too little and too much: hypoactivation and disinhibition of medial prefrontal cortex cause attentional deficits

Attentional deficits are core symptoms of schizophrenia, contributing strongly to disability. Prefrontal dysfunction has emerged as a candidate mechanism, with clinical evidence for prefrontal hypoactivation and disinhibition (reduced GABAergic inhibition), possibly reflecting different patient subpopulations. Here, we tested in rats whether imbalanced prefrontal neural activity impairs attention. To induce prefrontal hypoactivation or disinhibition, we microinfused the GABA-A receptor agonist muscimol (C4H6N2O2; 62.5, 125, 250 ng/side) or antagonist picrotoxin (C30H34O13; 75, 150, 300 ng/side), respectively, into the medial prefrontal cortex. Using the five-choice serial reaction time (5CSRT) test, we showed that both muscimol and picrotoxin impaired attention (reduced accuracy, increased omissions). Muscimol also impaired response control (increased premature responses). In addition, muscimol dose dependently reduced open-field locomotor activity, whereas 300 ng of picrotoxin caused locomotor hyperactivity; sensorimotor gating (startle prepulse inhibition) was unaffected. Therefore, infusion effects on the 5CSRT test can be dissociated from sensorimotor effects. Combining microinfusions with in vivo electrophysiology, we showed that muscimol inhibited prefrontal firing, whereas picrotoxin increased firing, mainly within bursts. Muscimol reduced and picrotoxin enhanced bursting and both drugs changed the temporal pattern of bursting. Picrotoxin also markedly enhanced prefrontal LFP power. Therefore, prefrontal hypoactivation and disinhibition both cause attentional deficits. Considering the electrophysiological findings, this suggests that attention requires appropriately tuned prefrontal activity. Apart from attentional deficits, prefrontal disinhibition caused additional neurobehavioral changes that may be relevant to schizophrenia pathophysiology, including enhanced prefrontal bursting and locomotor hyperactivity, which have been linked to psychosis-related dopamine hyperfunction.

GABA actions and ionic plasticity in epilepsy

Concepts of epilepsy, based on a simple change in neuronal excitation/inhibition balance, have subsided in face of recent insights into the large diversity and context-dependence of signaling mechanisms at the molecular, cellular and neuronal network level. GABAergic transmission exerts both seizure-suppressing and seizure-promoting actions. These two roles are prone to short-term and long-term alterations, evident both during epileptogenesis and during individual epileptiform events. The driving force of GABAergic currents is controlled by ion-regulatory molecules such as the neuronal K-Cl cotransporter KCC2 and cytosolic carbonic anhydrases. Accumulating evidence suggests that neuronal ion regulation is highly plastic, thereby contributing to the multiple roles ascribed to GABAergic signaling during epileptogenesis and epilepsy.

Glutamate-bound NMDARs arising from in vivo-like network activity extend spatio-temporal integration in a L5 cortical pyramidal cell model

In vivo, cortical pyramidal cells are bombarded by asynchronous synaptic input arising from ongoing network activity. However, little is known about how such 'background' synaptic input interacts with nonlinear dendritic mechanisms. We have modified an existing model of a layer 5 (L5) pyramidal cell to explore how dendritic integration in the apical dendritic tuft could be altered by the levels of network activity observed in vivo. Here we show that asynchronous background excitatory input increases neuronal gain and extends both temporal and spatial integration of stimulus-evoked synaptic input onto the dendritic tuft. Addition of fast and slow inhibitory synaptic conductances, with properties similar to those from dendritic targeting interneurons, that provided a 'balanced' background configuration, partially counteracted these effects, suggesting that inhibition can tune spatio-temporal integration in the tuft. Excitatory background input lowered the threshold for NMDA receptor-mediated dendritic spikes, extended their duration and increased the probability of additional regenerative events occurring in neighbouring branches. These effects were also observed in a passive model where all the non-synaptic voltage-gated conductances were removed. Our results show that glutamate-bound NMDA receptors arising from ongoing network activity can provide a powerful spatially distributed nonlinear dendritic conductance. This may enable L5 pyramidal cells to change their integrative properties as a function of local network activity, potentially allowing both clustered and spatially distributed synaptic inputs to be integrated over extended timescales.

Small modifications to network topology can induce stochastic bistable spiking dynamics in a balanced cortical model

Directed random graph models frequently are used successfully in modeling the population dynamics of networks of cortical neurons connected by chemical synapses. Experimental results consistently reveal that neuronal network topology is complex, however, in the sense that it differs statistically from a random network, and differs for classes of neurons that are physiologically different. This suggests that complex network models whose subnetworks have distinct topological structure may be a useful, and more biologically realistic, alternative to random networks. Here we demonstrate that the balanced excitation and inhibition frequently observed in small cortical regions can transiently disappear in otherwise standard neuronal-scale models of fluctuation-driven dynamics, solely because the random network topology was replaced by a complex clustered one, whilst not changing the in-degree of any neurons. In this network, a small subset of cells whose inhibition comes only from outside their local cluster are the cause of bistable population dynamics, where different clusters of these cells irregularly switch back and forth from a sparsely firing state to a highly active state. Transitions to the highly active state occur when a cluster of these cells spikes sufficiently often to cause strong unbalanced positive feedback to each other. Transitions back to the sparsely firing state rely on occasional large fluctuations in the amount of non-local inhibition received. Neurons in the model are homogeneous in their intrinsic dynamics and in-degrees, but differ in the abundance of various directed feedback motifs in which they participate. Our findings suggest that (i) models and simulations should take into account complex structure that varies for neuron and synapse classes; (ii) differences in the dynamics of neurons with similar intrinsic properties may be caused by their membership in distinctive local networks; (iii) it is important to identify neurons that share physiological properties and location, but differ in their connectivity.

Excitability and responsiveness of rat barrel cortex neurons in the presence and absence of spontaneous synaptic activity in vivo

The amplitude and temporal dynamics of spontaneous synaptic activity in the cerebral cortex vary as a function of brain states. To directly assess the impact of different ongoing synaptic activities on neocortical function, we performed in vivo intracellular recordings from barrel cortex neurons in rats under two pharmacological conditions generating either oscillatory or tonic synaptic drive. Cortical neurons membrane excitability and firing responses were compared, in the same neurons, before and after complete suppression of background synaptic drive following systemic injection of a high dose of anaesthetic. Compared to the oscillatory state, the tonic pattern resulted in a more depolarized and less fluctuating membrane potential (Vm), a lower input resistance (Rm) and steeper relations of firing frequency versus injected current (F-I). Whatever their temporal dynamics, suppression of background synaptic activities increased mean Vm, without affecting Rm, and induced a rightward shift of F-I curves. Both types of synaptic drive generated a high variability in current-induced firing rate and patterns in cortical neurons, which was much reduced after removal of spontaneous activity. These findings suggest that oscillatory and tonic synaptic patterns differentially facilitate the input-output function of cortical neurons but result in a similar moment-to-moment variability in spike responses to incoming depolarizing inputs.

GABAergic synapses: their plasticity and role in sensory cortex

The mammalian neocortex is composed of a variety of cell types organized in a highly interconnected circuit. GABAergic neurons account for only about 20% of cortical neurons. However, they show widespread connectivity and a high degree of diversity in morphology, location, electrophysiological properties and gene expression. In addition, distinct populations of inhibitory neurons have different sensory response properties, capacities for plasticity and sensitivities to changes in sensory experience. In this review we summarize experimental evidence regarding the properties of GABAergic neurons in primary sensory cortex. We will discuss how distinct GABAergic neurons and different forms of GABAergic inhibitory plasticity may contribute to shaping sensory cortical circuit activity and function.

Rapid dynamic changes of dendritic inhibition in the dentate gyrus by presynaptic activity patterns

The dentate gyrus (DG) serves as a primary gate to control information transfer from the cortex to the hippocampus. Activation of incoming cortical inputs results in rapid synaptic excitation followed by slow GABA-mediated (GABAergic) synaptic inhibition onto DG granule cells (GCs). GABAergic inhibitory interneurons (INs) in the DG comprise fast-spiking (FS) and non-fast-spiking (non-FS) cells. Anatomical analyses of DG INs reveal that FS cells are soma-targeting INs, whereas non-FS cells are dendrite-targeting INs. These two IN classes are differentially recruited by excitatory inputs and in turn provide exquisite spatiotemporal control over GC activity. Yet, little is known how FS and non-FS cells transform their presynaptic dynamics into varying postsynaptic response amplitudes. Using paired recordings in rat hippocampal slices, we show that inhibition in the DG is dominated by somatic GABAergic inputs during periods of sparse presynaptic activity, whereas dendritic GABAergic inputs are rapidly shifted to powerful and sustained inhibition during periods of intense presynaptic activity. The variant dynamics of dendritic inhibition is dependent on presynaptic IN subtypes and their activity patterns and is attributed to Ca(2+)-dependent increases in the probability of release and the size of the readily releasable pool. Furthermore, the degree of dynamic GABA release can be reduced by blocking voltage-gated K(+) channels, which increases the efficacy of dendrite-targeting IN output synapses during sparse firing. Such rapid dynamic modulation of dendritic inhibition may act as a frequency-dependent filter to prevent overexcitation of GC dendrites and thus set the excitatory-inhibitory synaptic balance in the DG circuits.

Oscillatory dynamics track motor performance improvement in human cortex

Improving performance in motor skill acquisition is proposed to be supported by tuning of neural networks. To address this issue we investigated changes of phase-amplitude cross-frequency coupling (paCFC) in neuronal networks during motor performance improvement. We recorded intracranially from subdural electrodes (electrocorticogram; ECoG) from 6 patients who learned 3 distinct motor tasks requiring coordination of finger movements with an external cue (serial response task, auditory motor coordination task, go/no-go). Performance improved in all subjects and all tasks during the first block and plateaued in subsequent blocks. Performance improvement was paralled by increasing neural changes in the trial-to-trial paCFC between theta (; 4–8 Hz) phase and high gamma (HG; 80–180 Hz) amplitude. Electrodes showing this covariation pattern (Pearson's r ranging up to .45) were located contralateral to the limb performing the task and were observed predominantly in motor brain regions. We observed stable paCFC when task performance asymptoted. Our results indicate that motor performance improvement is accompanied by adjustments in the dynamics and topology of neuronal network interactions in the and HG range. The location of the involved electrodes suggests that oscillatory dynamics in motor cortices support performance improvement with practice.

Dysregulation of group-I metabotropic glutamate (mGlu) receptor mediated signalling in disorders associated with Intellectual Disability and Autism

Activation of group-I metabotropic glutamate receptors, mGlu1 and mGlu5, triggers a variety of signalling pathways in neurons and glial cells, which are differently implicated in synaptic plasticity. The earliest and much of key studies discovered abnormal mGlu5 receptor function in Fragile X syndrome (FXS) mouse models which then motivated more recent work that finds mGlu5 receptor dysfunction in related disorders such as intellectual disability (ID), obsessive-compulsive disorder (OCD) and autism. Therefore, mGlu1/5 receptor dysfunction may represent a common aetiology of these complex diseases. Furthermore, many studies have focused on dysregulation of mGlu5 signalling to synaptic protein synthesis. However, emerging evidence finds abnormal mGlu5 receptor interactions with its scaffolding proteins in FXS which results in mGlu5 receptor dysfunction and phenotypes independent of signalling to protein synthesis. Finally, both an increased and reduced mGlu5 functioning seem to be associated with ID and autism spectrum disorders, with important consequences for potential treatment of these developmental disorders.

Cortical activity in the null space: permitting preparation without movement

Neural circuits must perform computations and then selectively output the results to other circuits. Yet synapses do not change radically at millisecond timescales. A key question then is: how is communication between neural circuits controlled? In motor control, brain areas directly involved in driving movement are active well before movement begins. Muscle activity is some readout of neural activity, yet remains largely unchanged during preparation. Here we find that during preparation, while the monkey holds still, changes in motor cortical activity cancel out at the level of these population readouts. Motor cortex can thereby prepare the movement without prematurely causing it. Further, we found evidence that this mechanism also operates in dorsal premotor cortex (PMd), largely accounting for how preparatory activity is attenuated in primary motor cortex (M1). Selective use of “output-null” vs. “output-potent” patterns of activity may thus help control communication to the muscles and between these brain areas.

Oscillatory activity in neocortical networks during tactile discrimination near the limit of spatial acuity

Oscillatory interactions within functionally specialized but distributed brain regions are believed to be central to perceptual and cognitive functions. Here, using human scalp electroencephalography (EEG) recordings combined with source reconstruction techniques, we study how oscillatory activity functionally organizes different neocortical regions during a tactile discrimination task near the limit of spatial acuity. While undergoing EEG recordings, blindfolded participants felt a linear three-dot array presented electromechanically, under computer control, and reported whether the central dot was offset to the left or right. The average brain response differed significantly for trials with correct and incorrect perceptual responses in the timeframe approximately between 130 and 175ms. During trials with correct responses, source-level peak activity appeared in the left primary somatosensory cortex (SI) at around 45ms, in the right lateral occipital complex (LOC) at 130ms, in the right posterior intraparietal sulcus (pIPS) at 160ms, and finally in the left dorsolateral prefrontal cortex (dlPFC) at 175ms. Spectral interdependency analysis of activity in these nodes showed two distinct distributed networks, a dominantly feedforward network in the beta band (12-30Hz) that included all four nodes and a recurrent network in the gamma band (30-100Hz) that linked SI, pIPS and dlPFC. Measures of network activity in both bands were correlated with the accuracy of task performance. These findings suggest that beta and gamma band oscillatory networks coordinate activity between neocortical regions mediating sensory and cognitive processing to arrive at tactile perceptual decisions.

Cumulative latency advance underlies fast visual processing in desynchronized brain state

Fast sensory processing is vital for the animal to efficiently respond to the changing environment. This is usually achieved when the animal is vigilant, as reflected by cortical desynchronization. However, the neural substrate for such fast processing remains unclear. Here, we report that neurons in rat primary visual cortex (V1) exhibited shorter response latency in the desynchronized state than in the synchronized state. In vivo whole-cell recording from the same V1 neurons undergoing the two states showed that both the resting and visually evoked conductances were higher in the desynchronized state. Such conductance increases of single V1 neurons shorten the response latency by elevating the membrane potential closer to the firing threshold and reducing the membrane time constant, but the effects only account for a small fraction of the observed latency advance. Simultaneous recordings in lateral geniculate nucleus (LGN) and V1 revealed that LGN neurons also exhibited latency advance, with a degree smaller than that of V1 neurons. Furthermore, latency advance in V1 increased across successive cortical layers. Thus, latency advance accumulates along various stages of the visual pathway, likely due to a global increase of membrane conductance in the desynchronized state. This cumulative effect may lead to a dramatic shortening of response latency for neurons in higher visual cortex and play a critical role in fast processing for vigilant animals.

Increased firing irregularity as an emergent property of neural-state transition in monkey prefrontal cortex

Flexible behaviors are organized by complex neural networks in the prefrontal cortex. Recent studies have suggested that such networks exhibit multiple dynamical states, and can switch rapidly from one state to another. In many complex systems such as the brain, the early-warning signals that may predict whether a critical threshold for state transitions is approaching are extremely difficult to detect. We hypothesized that increases in firing irregularity are a crucial measure for predicting state transitions in the underlying neuronal circuits of the prefrontal cortex. We used both experimental and theoretical approaches to test this hypothesis. Experimentally, we analyzed activities of neurons in the prefrontal cortex while monkeys performed a maze task that required them to perform actions to reach a goal. We observed increased firing irregularity before the activity changed to encode goal-to-action information. Theoretically, we constructed theoretical generic neural networks and demonstrated that changes in neuronal gain on functional connectivity resulted in a loss of stability and an altered state of the networks, accompanied by increased firing irregularity. These results suggest that assessing the temporal pattern of neuronal fluctuations provides important clues regarding the state stability of the prefrontal network. We also introduce a novel scheme that the prefrontal cortex functions in a metastable state near the critical point of bifurcation. According to this scheme, firing irregularity in the prefrontal cortex indicates that the system is about to change its state and the flow of information in a flexible manner, which is essential for executive functions. This metastable and/or critical dynamical state of the prefrontal cortex may account for distractibility and loss of flexibility in the prefrontal cortex in major mental illnesses such as schizophrenia.

Evidence for dysregulated high-frequency oscillations during sensory processing in medication-naïve, first episode schizophrenia

INTRODUCTION

High-frequency oscillations are important for sensory processing and dysfunctions in the amplitude and synchrony of beta- and gamma-band oscillations have been demonstrated in schizophrenia (ScZ). However, the presence of aberrant high-frequency oscillations in first-episode (FE), medication-naive patients during sensory processing is unclear.

METHODS

Magnetoencephalographic (MEG) data were recorded from 15 never-medicated, FE-ScZ patients and 20 matched healthy controls during the perception of Mooney faces. MEG data were analysed for spectral power and single-sensor phase-locking in the beta (13-25Hz) and gamma- (25-140Hz) frequency range.

RESULTS

FE-ScZ patients were characterized by significantly impaired sensory processing as indicated by a reduced discrimination index (A'). Impaired behavioural performance in ScZ-patients was accompanied by decreased spectral power in the high- (60-120Hz) gamma-band range. In contrast, oscillations in the lower (25-60Hz) gamma-band were largely intact and beta-band oscillations were increased. Analysis of cross-frequency coupling showed a reduced correlation between 60 and 120Hz amplitude values and beta-band power in FE-ScZ-patients relative to controls.

DISCUSSION

Our findings show that impaired sensory processing in medication-naive, FE-schizophrenia is related to a dysregulation of neural oscillations which involves both an impairment in the generation of high gamma-band activity as well as a failure to downregulate task-irrelevant beta-band activity. Because of the interrelationship of these dysfunctions and the role of inhibitory networks in the shaping of high-frequency activity, aberrant neural oscillations in FE-schizophrenia may be linked to dysfunctions in the excitation-inhibition (E/I)-balance.

Prefrontal cortex HCN1 channels enable intrinsic persistent neural firing and executive memory function

In many cortical neurons, HCN1 channels are the major contributors to Ih, the hyperpolarization-activated current, which regulates the intrinsic properties of neurons and shapes their integration of synaptic inputs, paces rhythmic activity, and regulates synaptic plasticity. Here, we examine the physiological role of Ih in deep layer pyramidal neurons in mouse prefrontal cortex (PFC), focusing on persistent activity, a form of sustained firing thought to be important for the behavioral function of the PFC during working memory tasks. We find that HCN1 contributes to the intrinsic persistent firing that is induced by a brief depolarizing current stimulus in the presence of muscarinic agonists. Deletion of HCN1 or acute pharmacological blockade of Ih decreases the fraction of neurons capable of generating persistent firing. The reduction in persistent firing is caused by the membrane hyperpolarization that results from the deletion of HCN1 or Ih blockade, rather than a specific role of the hyperpolarization-activated current in generating persistent activity. In vivo recordings show that deletion of HCN1 has no effect on up states, periods of enhanced synaptic network activity. Parallel behavioral studies demonstrate that HCN1 contributes to the PFC-dependent resolution of proactive interference during working memory. These results thus provide genetic evidence demonstrating the importance of HCN1 to intrinsic persistent firing and the behavioral output of the PFC. The causal role of intrinsic persistent firing in PFC-mediated behavior remains an open question.

Emergence of metastable state dynamics in interconnected cortical networks with propagation delays

The importance of the large number of thin-diameter and unmyelinated axons that connect different cortical areas is unknown. The pronounced propagation delays in these axons may prevent synchronization of cortical networks and therefore hinder efficient information integration and processing. Yet, such global information integration across cortical areas is vital for higher cognitive function. We hypothesized that delays in communication between cortical areas can disrupt synchronization and therefore enhance the set of activity trajectories and computations interconnected networks can perform. To evaluate this hypothesis, we studied the effect of long-range cortical projections with propagation delays in interconnected large-scale cortical networks that exhibited spontaneous rhythmic activity. Long-range connections with delays caused the emergence of metastable, spatio-temporally distinct activity states between which the networks spontaneously transitioned. Interestingly, the observed activity patterns correspond to macroscopic network dynamics such as globally synchronized activity, propagating wave fronts, and spiral waves that have been previously observed in neurophysiological recordings from humans and animal models. Transient perturbations with simulated transcranial alternating current stimulation (tACS) confirmed the multistability of the interconnected networks by switching the networks between these metastable states. Our model thus proposes that slower long-range connections enrich the landscape of activity states and represent a parsimonious mechanism for the emergence of multistability in cortical networks. These results further provide a mechanistic link between the known deficits in connectivity and cortical state dynamics in neuropsychiatric illnesses such as schizophrenia and autism, as well as suggest non-invasive brain stimulation as an effective treatment for these illnesses.

Transcranial alternating current stimulation modulates large-scale cortical network activity by network resonance

Transcranial direct current stimulation (tDCS) has emerged as a potentially safe and effective brain stimulation modality that alters cortical excitability by passing a small, constant electric current through the scalp. tDCS creates an electric field that weakly modulates the membrane voltage of a large number of cortical neurons. Recent human studies have suggested that sine-wave stimulation waveforms [transcranial alternating current stimulation (tACS)] represent a more targeted stimulation paradigm for the enhancement of cortical oscillations. Yet, the underlying mechanisms of how periodic, weak global perturbations alter the spatiotemporal dynamics of large-scale cortical network dynamics remain a matter of debate. Here, we simulated large-scale networks of spiking neuron models to address this question in endogenously rhythmic networks. We identified distinct roles of the depolarizing and hyperpolarizing phases of tACS in entrainment, which entailed moving network activity toward and away from a strong nonlinearity provided by the local excitatory coupling of pyramidal cells. Together, these mechanisms gave rise to resonance dynamics characterized by an Arnold tongue centered on the resonance frequency of the network. We then performed multichannel extracellular recordings of multiunit firing activity during tACS in anesthetized ferrets (Mustela putoris furo), a model species with a gyrencephalic brain, to verify that weak global perturbations can selectively enhance oscillations at the applied stimulation frequency. Together, these results provide a detailed mechanistic understanding of tACS at the level of large-scale network dynamics and support the future design of activity-dependent feedback tACS paradigms that dynamically tailor stimulation frequency to the spectral peak of ongoing brain activity.

High-frequency oscillations and the neurobiology of schizophrenia

Neural oscillations at low- and high-frequency ranges are a fundamental feature of large-scale networks. Recent evidence has indicated that schizophrenia is associated with abnormal amplitude and synchrony of oscillatory activity, in particular, at high (beta/gamma) frequencies. These abnormalities are observed during task-related and spontaneous neuronal activity which may be important for understanding the pathophysiology of the syndrome. In this paper, we shall review the current evidence for impaired beta/gamma-band oscillations and their involvement in cognitive functions and certain symptoms of the disorder. In the first part, we will provide an update on neural oscillations during normal brain functions and discuss underlying mechanisms. This will be followed by a review of studies that have examined high-frequency oscillatory activity in schizophrenia and discuss evidence that relates abnormalities of oscillatory activity to disturbed excitatory/inhibitory (E/I) balance. Finally, we shall identify critical issues for future research in this area.

Balanced cortical microcircuitry for maintaining information in working memory

Persistent neural activity in the absence of a stimulus has been identified as a neural correlate of working memory, but how such activity is maintained by neocortical circuits remains unknown. Here we show that the inhibitory and excitatory microcircuitry of neocortical memory-storing regions is sufficient to implement a corrective feedback mechanism that enables persistent activity to be maintained stably for prolonged durations. When recurrent excitatory and inhibitory inputs to memory neurons are balanced in strength, but offset in time, drifts in activity trigger a corrective signal that counteracts memory decay. Circuits containing this mechanism temporally integrate their inputs, generate the irregular neural firing observed during persistent activity, and are robust against common perturbations that severely disrupt previous models of short-term memory storage. This work reveals a mechanism for the accumulation and storage of memories in neocortical circuits based upon principles of corrective negative feedback widely used in engineering applications.

The aging motor system as a model for plastic changes of GABA-mediated intracortical inhibition and their behavioral relevance

Since GABAA-mediated intracortical inhibition has been shown to underlie plastic changes throughout the lifespan from development to aging, here, the aging motor system was used as a model to analyze the interdependence of plastic alterations within the inhibitory motorcortical network and level of behavioral performance. Double-pulse transcranial magnetic stimulation (dpTMS) was used to examine inhibition by means of short-interval intracortical inhibition (SICI) of the contralateral primary motor cortex in a sample of 64 healthy right-handed human subjects covering a wide range of the adult lifespan (age range 20-88 years, mean 47.6 ± 20.7, 34 female). SICI was evaluated during resting state and in an event-related condition during movement preparation in a visually triggered simple reaction time task. In a subgroup (N = 23), manual motor performance was tested with tasks of graded dexterous demand. Weak resting-state inhibition was associated with an overall lower manual motor performance. Better event-related modulation of inhibition correlated with better performance in more demanding tasks, in which fast alternating activation of cortical representations are necessary. Declining resting-state inhibition was associated with weakened event-related modulation of inhibition. Therefore, reduced resting-state inhibition might lead to a subsequent loss of modulatory capacity, possibly reflecting malfunctioning precision in GABAAergic neurotransmission; the consequence is an inevitable decline in motor function.

Motor cortex feedback influences sensory processing by modulating network state

Long-range corticocortical communication may have important roles in context-dependent sensory processing, yet we know very little about how these pathways influence their target regions. We studied the influence of primary motor cortex activity on primary somatosensory cortex in the mouse whisker system. We show that primary motor and somatosensory cortices undergo coherent, context-dependent changes in network state. Moreover, we show that motor cortex activity can drive changes in somatosensory cortex network state. A series of experiments demonstrate the involvement of the direct corticocortical feedback pathway, providing temporally precise and spatially targeted modulation of network dynamics. Cortically mediated changes in network state significantly impact sensory coding, with activated states increasing the reliability of responses to complex stimuli. By influencing network state, corticocortical communication from motor cortex may ensure that during active exploration the relevant sensory region is primed for enhanced sensory discrimination.

CaV 2.1 ablation in cortical interneurons selectively impairs fast-spiking basket cells and causes generalized seizures

OBJECTIVE

Both the neuronal populations and mechanisms responsible for generalized spike-wave absence seizures are poorly understood. In mutant mice carrying loss-of-function (LOF) mutations in Cacna1a, which encodes the α1 pore-forming subunit of CaV 2.1 (P/Q-type) voltage-gated Ca(2+) channels, generalized spike-wave seizures have been suggested to result from excessive bursting of thalamocortical cells. However, other cellular populations including cortical inhibitory interneurons may contribute to this phenotype. We investigated how different cortical interneuron subtypes are affected by the loss of CaV 2.1 channel function and how this contributes to the onset of generalized epilepsy.

METHODS

We designed genetic strategies to induce a selective Cacna1a LOF mutation in different cortical γ-aminobutyric acidergic (GABAergic) and/or glutamatergic neuronal populations in mice. We assessed the cellular and network consequences of these mutations by combining immunohistochemical assays, in vitro physiology, optogenetics, and in vivo video electroencephalographic recordings.

RESULTS

We demonstrate that selective Cacna1a LOF from a subset of cortical interneurons, including parvalbumin (PV)(+) and somatostatin (SST)(+) interneurons, results in severe generalized epilepsy. Loss of CaV 2.1 channel function compromises GABA release from PV(+) but not SST(+) interneurons. Moreover, thalamocortical projection neurons do not show enhanced bursting in these mutants, suggesting that this feature is not essential for the development of generalized spike-wave seizures. Notably, the concurrent removal of CaV 2.1 channels in cortical pyramidal cells and interneurons considerably lessens seizure severity by decreasing cortical excitability.

INTERPRETATION

Our findings demonstrate that conditional ablation of CaV 2.1 channel function from cortical PV(+) interneurons alters GABA release from these cells, impairs their ability to constrain cortical pyramidal cell excitability, and is sufficient to cause generalized seizures.

Transformation of the neural code for tactile detection from thalamus to cortex

To understand how sensory-driven neural activity gives rise to perception, it is essential to characterize how various relay stations in the brain encode stimulus presence. Neurons in the ventral posterior lateral (VPL) nucleus of the somatosensory thalamus and in primary somatosensory cortex (S1) respond to vibrotactile stimulation with relatively slow modulations (∼100 ms) of their firing rate. In addition, faster modulations (∼10 ms) time-locked to the stimulus waveform are observed in both areas, but their contribution to stimulus detection is unknown. Furthermore, it is unclear whether VPL and S1 neurons encode stimulus presence with similar accuracy and via the same response features. To address these questions, we recorded single neurons while trained monkeys judged the presence or absence of a vibrotactile stimulus of variable amplitude, and their activity was analyzed with a unique decoding method that is sensitive to the time scale of the firing rate fluctuations. We found that the maximum detection accuracy of single neurons is similar in VPL and S1. However, VPL relies more heavily on fast rate modulations than S1, and as a consequence, the neural code in S1 is more tolerant: its performance degrades less when the readout method or the time scale of integration is suboptimal. Therefore, S1 neurons implement a more robust code, one less sensitive to the temporal integration window used to infer stimulus presence downstream. The differences between VPL and S1 responses signaling the appearance of a stimulus suggest a transformation of the neural code from thalamus to cortex.

The effects of neural gain on attention and learning

Attention is commonly thought to be manifest through local variations in neural gain. However, what would be the effects of brain-wide changes in gain? Here, we hypothesize that global fluctuations in gain modulate the breadth of attention, and thus, the degree to which processing is focused on aspects of the environment to which one is predisposed to attend. In accordance with this hypothesis, we show that measures of pupil diameter, which are thought to track levels of LC-NE activity and neural gain, are correlated with the degree to which learning is focused on stimulus dimensions that individual human participants are more predisposed to process. In support of our interpretation of this effect in terms of global changes in gain, we further show that the measured pupillary and behavioral variables are strongly correlated with global changes in the strength and clustering of functional connectivity, as brain-wide fluctuations of gain would predict.

Sublinear integration underlies binocular processing in primary visual cortex

Although we know much about the capacity of neurons to integrate synaptic inputs in vitro, less is known about synaptic integration in vivo. Here we address this issue by investigating the integration of inputs from the two eyes in mouse primary visual cortex. We find that binocular inputs to layer 2/3 pyramidal neurons are integrated sublinearly in an amplitude-dependent manner. Sublinear integration was greatest when binocular responses were largest, as occurs at the preferred orientation and binocular disparity, and highest contrast. Using voltage-clamp experiments and modeling, we show that sublinear integration occurs postsynaptically. The extent of sublinear integration cannot be accounted for solely by nonlinear integration of excitatory inputs, even when they are activated closely in space and time, but requires balanced recruitment of inhibition. Finally, we show that sublinear binocular integration acts as a divisive form of gain control, linearizing the output of binocular neurons and enhancing orientation selectivity.

Development and specification of GABAergic cortical interneurons

GABAergic interneurons are inhibitory neurons of the nervous system that play a vital role in neural circuitry and activity. They are so named due to their release of the neurotransmitter gamma-aminobutyric acid (GABA), and occupy different areas of the brain. This review will focus primarily on GABAergic interneurons of the mammalian cerebral cortex from a developmental standpoint. There is a diverse amount of cortical interneuronal subtypes that may be categorized by a number of characteristics; this review will classify them largely by the protein markers they express. The developmental origins of GABAergic interneurons will be discussed, as well as factors that influence the complex migration routes that these interneurons must take in order to ultimately localize in the cerebral cortex where they will integrate with the neural circuitry set in place. This review will also place an emphasis on the transcriptional network of genes that play a role in the specification and maintenance of GABAergic interneuron fate. Gaining an understanding of the different aspects of cortical interneuron development and specification, especially in humans, has many useful clinical applications that may serve to treat various neurological disorders linked to alterations in interneuron populations.

Functional circuits and anatomical distribution of response properties in the primate amygdala

Recent electrophysiological studies on the primate amygdala have advanced our understanding of how individual neurons encode information relevant to emotional processes, but it remains unclear how these neurons are functionally and anatomically organized. To address this, we analyzed cross-correlograms of amygdala spike trains recorded during a task in which monkeys learned to associate novel images with rewarding and aversive outcomes. Using this task, we have recently described two populations of amygdala neurons: one that responds more strongly to images predicting reward (positive value-coding), and another that responds more strongly to images predicting an aversive stimulus (negative value-coding). Here, we report that these neural populations are organized into distinct, but anatomically intermingled, appetitive and aversive functional circuits, which are dynamically modulated as animals used the images to predict outcomes. Furthermore, we report that responses to sensory stimuli are prevalent in the lateral amygdala, and are also prevalent in the medial amygdala for sensory stimuli that are emotionally significant. The circuits identified here could potentially mediate valence-specific emotional behaviors thought to involve the amygdala.

Chronic electrical stimulation homeostatically decreases spontaneous activity, but paradoxically increases evoked network activity

Neural dynamics generated within cortical networks play a fundamental role in brain function. However, the learning rules that allow recurrent networks to generate functional dynamic regimes, and the degree to which these regimes are themselves plastic, are not known. In this study we examined plasticity of network dynamics in cortical organotypic slices in response to chronic changes in activity. Studies have typically manipulated network activity pharmacologically; we used chronic electrical stimulation to increase activity in in vitro cortical circuits in a more physiological manner. Slices were stimulated with "implanted" electrodes for 4 days. Chronic electrical stimulation or treatment with bicuculline decreased spontaneous activity as predicted by homeostatic learning rules. Paradoxically, however, whereas bicuculline decreased evoked network activity, chronic stimulation actually increased the likelihood that evoked stimulation elicited polysynaptic activity, despite a decrease in evoked monosynaptic strength. Furthermore, there was an inverse correlation between spontaneous and evoked activity, suggesting a homeostatic tradeoff between spontaneous and evoked activity. Within-slice experiments revealed that cells close to the stimulated electrode exhibited more evoked polysynaptic activity and less spontaneous activity than cells close to a control electrode. Collectively, our results establish that chronic stimulation changes the dynamic regimes of networks. In vitro studies of homeostatic plasticity typically lack any external input, and thus neurons must rely on "spontaneous" activity to reach homeostatic "set points." However, in the presence of external input we propose that homeostatic learning rules seem to shift networks from spontaneous to evoked regimes.

Inhibition dominates sensory responses in the awake cortex

The activity of the cerebral cortex is thought to depend on the precise relationship between synaptic excitation and inhibition. In the visual cortex, in particular, intracellular measurements have related response selectivity to coordinated increases in excitation and inhibition. These measurements, however, have all been made during anaesthesia, which strongly influences cortical state and therefore sensory processing. The synaptic activity that is evoked by visual stimulation during wakefulness is unknown. Here we measured visually evoked responses--and the underlying synaptic conductances--in the visual cortex of anaesthetized and awake mice. Under anaesthesia, responses could be elicited from a large region of visual space and were prolonged. During wakefulness, responses were more spatially selective and much briefer. Whole-cell patch-clamp recordings of synaptic conductances showed a difference in synaptic inhibition between the two conditions. Under anaesthesia, inhibition tracked excitation in amplitude and spatial selectivity. By contrast, during wakefulness, inhibition was much stronger than excitation and had extremely broad spatial selectivity. We conclude that during wakefulness, cortical responses to visual stimulation are dominated by synaptic inhibition, restricting the spatial spread and temporal persistence of neural activity. These results provide a direct glimpse of synaptic mechanisms that control sensory responses in the awake cortex.

Central thalamic deep brain stimulation for support of forebrain arousal regulation in the minimally conscious state

This chapter considers the use of central thalamic deep brain stimulation (CT/DBS) to support arousal regulation mechanisms in the minimally conscious state (MCS). CT/DBS for selected patients in a MCS is first placed in the historical context of prior efforts to use thalamic electrical brain stimulation to treat the unconscious clinical conditions of coma and vegetative state. These previous studies and a proof of concept result from a single-subject study of a patient in a MCS are reviewed against the background of new population data providing benchmarks of the natural history of vegetative and MCSs. The conceptual foundations for CT/DBS in selected patients in a MCS are then presented with consideration of both circuit and cellular mechanisms underlying recovery of consciousness identified from empirical studies. Directions for developing future generalizable criteria for CT/DBS that focus on the integrity of necessary brain systems and behavioral profiles in patients in a MCS that may optimally response to support of arousal regulation mechanisms are proposed.

Laminar-dependent effects of cortical state on auditory cortical spontaneous activity

Cortical circuits spontaneously generate coordinated activity even in the absence of external inputs. The character of this activity depends on cortical state. We investigated how state affects the organization of spontaneous activity across layers of rat auditory cortex in vivo, using juxtacellular recording of morphologically identified neurons and large-scale electrophysiological recordings. Superficial pyramidal cells (PCs) and putative fast-spiking interneurons (FSs) were consistently suppressed during cortical desynchronization. PCs in deep layers showed heterogeneous responses to desynchronization, with some cells showing increased rates, typically large tufted PCs of high baseline firing rate, but not FSs. Consistent results were found between desynchronization occurring spontaneously in unanesthetized animals, and desynchronization evoked by electrical stimulation of the pedunculopontine tegmental (PPT) nucleus under urethane anesthesia. We hypothesize that reduction in superficial layer firing may enhance the brain's extraction of behaviorally relevant signals from noisy brain activity.

Transient sodium current at subthreshold voltages: activation by EPSP waveforms

Tetrodotoxin (TTX)-sensitive sodium channels carry large transient currents during action potentials and also "persistent" sodium current, a noninactivating TTX-sensitive current present at subthreshold voltages. We examined gating of subthreshold sodium current in dissociated cerebellar Purkinje neurons and hippocampal CA1 neurons, studied at 37°C with near-physiological ionic conditions. Unexpectedly, in both cell types small voltage steps at subthreshold voltages activated a substantial component of transient sodium current as well as persistent current. Subthreshold EPSP-like waveforms also activated a large component of transient sodium current, but IPSP-like waveforms engaged primarily persistent sodium current with only a small additional transient component. Activation of transient as well as persistent sodium current at subthreshold voltages produces amplification of EPSPs that is sensitive to the rate of depolarization and can help account for the dependence of spike threshold on depolarization rate, as previously observed in vivo.

Emergence in the central nervous system

"Emergence" is an idea that has received much attention in consciousness literature, but it is difficult to find characterizations of that concept which are both specific and useful. I will precisely define and characterize a type of epistemic ("weak") emergence and show that it is a property of some neural circuits throughout the CNS, on micro-, meso- and macroscopic levels. I will argue that possession of this property can result in profoundly altered neural dynamics on multiple levels in cortex and other systems. I will first describe emergent neural entities (ENEs) abstractly. I will then show how ENEs function specifically and concretely, and demonstrate some implications of this type of emergence for the CNS.

Selective functional interactions between excitatory and inhibitory cortical neurons and differential contribution to persistent activity of the slow oscillation

The neocortex depends upon a relative balance of recurrent excitation and inhibition for its operation. During spontaneous Up states, cortical pyramidal cells receive proportional barrages of excitatory and inhibitory synaptic potentials. Many of these synaptic potentials arise from the activity of nearby neurons, although the identity of these cells is relatively unknown, especially for those underlying the generation of inhibitory synaptic events. To address these fundamental questions, we developed an in vitro submerged slice preparation of the mouse entorhinal cortex that generates robust and regular spontaneous recurrent network activity in the form of the slow oscillation. By performing whole-cell recordings from multiple cell types identified with green fluorescent protein expression and electrophysiological and/or morphological properties, we show that distinct functional subpopulations of neurons exist in the entorhinal cortex, with large variations in contribution to the generation of balanced excitation and inhibition during the slow oscillation. The most active neurons during the slow oscillation are excitatory pyramidal and inhibitory fast spiking interneurons, receiving robust barrages of both excitatory and inhibitory synaptic potentials. Weak action potential activity was observed in stellate excitatory neurons and somatostatin-containing interneurons. In contrast, interneurons containing neuropeptide Y, vasoactive intestinal peptide, or the 5-hydroxytryptamine (serotonin) 3a receptor, were silent. Our data demonstrate remarkable functional specificity in the interactions between different excitatory and inhibitory cortical neuronal subtypes, and suggest that it is the large recurrent interaction between pyramidal neurons and fast spiking interneurons that is responsible for the generation of persistent activity that characterizes the depolarized states of the cortex.

Traveling waves in visual cortex

Electrode recordings and imaging studies have revealed that localized visual stimuli elicit waves of activity that travel across primary visual cortex. Traveling waves are present also during spontaneous activity, but they can be greatly reduced by widespread and intensive visual stimulation. In this Review, we summarize the evidence in favor of these traveling waves. We suggest that their substrate may lie in long-range horizontal connections and that their functional role may involve the integration of information over large regions of space.

Mechanisms of neuronal computation in mammalian visual cortex

Orientation selectivity in the primary visual cortex (V1) is a receptive field property that is at once simple enough to make it amenable to experimental and theoretical approaches and yet complex enough to represent a significant transformation in the representation of the visual image. As a result, V1 has become an area of choice for studying cortical computation and its underlying mechanisms. Here we consider the receptive field properties of the simple cells in cat V1--the cells that receive direct input from thalamic relay cells--and explore how these properties, many of which are highly nonlinear, arise. We have found that many receptive field properties of V1 simple cells fall directly out of Hubel and Wiesel's feedforward model when the model incorporates realistic neuronal and synaptic mechanisms, including threshold, synaptic depression, response variability, and the membrane time constant.

Neuronal circuits underlying persistent representations despite time varying activity

BACKGROUND

Our brains are capable of remarkably stable stimulus representations despite time-varying neural activity. For instance, during delay periods in working memory tasks, while stimuli are represented in working memory, neurons in the prefrontal cortex, thought to support the memory representation, exhibit time-varying neuronal activity. Since neuronal activity encodes the stimulus, its time-varying dynamics appears to be paradoxical and incompatible with stable network stimulus representations. Indeed, this finding raises a fundamental question: can stable representations only be encoded with stable neural activity, or, its corollary, is every change in activity a sign of change in stimulus representation?

RESULTS

Here we explain how different time-varying representations offered by individual neurons can be woven together to form a coherent, time-invariant, representation. Motivated by two ubiquitous features of the neocortex-redundancy of neural representation and sparse intracortical connections-we derive a network architecture that resolves the apparent contradiction between representation stability and changing neural activity. Unexpectedly, this network architecture exhibits many structural properties that have been measured in cortical sensory areas. In particular, we can account for few-neuron motifs, synapse weight distribution, and the relations between neuronal functional properties and connection probability.

CONCLUSIONS

We show that the intuition regarding network stimulus representation, typically derived from considering single neurons, may be misleading and that time-varying activity of distributed representation in cortical circuits does not necessarily imply that the network explicitly encodes time-varying properties.

Columnar distribution of activity dependent gabaergic depolarization in sensorimotor cortical neurons

Background

GABA, the major inhibitory neurotransmitter in CNS, has been demonstrated to paradoxically produce excitation even in mature brain. However activity-dependent form of GABA excitation in cortical neurons has not been observed. Here we report that after an intense electrical stimulation adult cortical neurons displayed a transient GABA excitation that lasted for about 30s.

Results

Whole-cell patch recordings were performed to evaluate the effects of briefly applied GABA on pyramidal neurons in adult rodent sensorimotor cortical slice before and after 1 s, 20 Hz suprathreshold electrical stimulation of the junction between layer 6 and the underlying white matter (L6/WM stimulation). Immediately after L6/WM stimulation, GABA puffs produced neuronal depolarization in the center of the column-shaped region. However, both prior to or 30s after stimulation GABA puffs produced hyperpolarization of neurons. 2-photon imaging in neurons infected with adenovirus carrying a chloride sensor Clomeleon revealed that GABA induced depolarization is due to an increase in [Cl^-]_i after stimulation. To reveal the spatial extent of excitatory action of GABA, isoguvacine, a GABA_A receptors agonist, was applied right after stimulation while monitoring the intracellular Ca²⁺ concentration in pyramidal neurons. Isoguvacine induced an increase in [Ca²⁺]_i in pyramidal neurons especially in the center of the column but not in the peripheral regions of the column. The global pattern of the Ca²⁺ signal showed a column-shaped distribution along the stimulation site.

Conclusion

These results demonstrate that the well-known inhibitory transmitter GABA rapidly switches from hyperpolarization to depolarization upon synaptic activity in adult somatosensory cortical neurons.

Frequency-invariant temporal ordering of interneuronal discharges during hippocampal oscillations in awake mice

Endogenous brain rhythms occurring at various frequencies and associated with distinct behavioral states provide multiscale temporal windows that enable cells to time their spiking activity with high precision, which is thought to be important for the coding of information in neuronal circuits. However, although the selective timing of GABAergic inputs to specific spatial domains of principal cells are known to play key roles in network oscillations, the in vivo firing patterns of distinct hippocampal interneurons in awake animals are not known. Here we used a combination of juxtacellular labeling techniques with recordings from anesthesia-free, head-fixed mice running or resting on a spherical treadmill to study the oscillation-dependent discharges by two major interneuronal subtypes, the perisomatically projecting parvalbumin-positive basket cells (PVBCs) and distal dendritically projecting oriens lacunosum moleculare (OLM) cells. Recordings of the spiking activity of post hoc-identified CA1 interneurons during theta (5-10 Hz), gamma (25-90Hz), epsilon ("high-gamma"; 90-130 Hz), and ripple (130-200 Hz) oscillations revealed both cell type- and behavioral state-dependent entrainments of PVBC and OLM cell discharges in awake mice. Our results in awake mice differed in several respects from previous data on interneuronal discharge patterns in anesthetized animals. In addition, our results demonstrate a form of frequency-invariant, cell type-specific temporal ordering of inhibitory inputs in which PVBC-derived perisomatic inhibition is followed by OLM cell-generated distal dendritic inhibition during each of the network oscillation bands studied, spanning more than an order of magnitude in frequencies.

Functional impact of interneuronal inhibition in the cerebral cortex of behaving animals

This paper reviews recent progress in understanding the functional roles of inhibitory interneurons in behaving animals and how they affect information processing in cortical microcircuits. Multiple studies have shown that the morphological subtypes of inhibitory cells show distinct electrophysiological properties, as well as different molecular and neurochemical identities, providing a large mosaic of inhibitory mechanisms for the dynamic processing of information in the cortex. However, it is only recently that some specific functions of different interneuronal subtypes have been described in behaving animals. In this regard, influential results have been obtained using the known differences of interneurons and pyramidal cells recorded extracellularly to dissociate the functional roles that these two classes of neurons may play in the cortical microcircuits during various behaviors. Neurons can be segregated into fast-spiking (FS) cells that show short action potentials, high discharge rates, and correspond to putative interneurons; and regular-spiking (RS) cells that show larger action potentials and correspond to pyramidal neurons. Using this classification strategy, it has been found that cortical inhibition is involved in sculpting the tuning to different stimulus or behavioral features across a wide variety of sensory, association, and motor areas. Recent studies have suggested that the increase in high-frequency synchronization during information processing and spatial attention may be mediated by FS activation. Finally, FS are active during motor planning and movement execution in different motor areas, supporting the notion that inhibitory interneurons are involved in shaping the motor command but not in gating the cortical output.

Local field potentials and border ownership: A conjecture about computation in visual cortex

Border ownership is an intermediate-level visual task: it must integrate (upward flowing) image information about edges with (downward flowing) shape information. This highlights the familiar local-to-global aspect of border formation (linking of edge elements to form contours) with the much less studied global-to-local aspect (which edge elements form part of the same shape). To address this task we show how to incorporate certain high-level notions of distance and geometric arrangement into a form that can influence image-based edge information. The center of the argument is a reaction-diffusion equation that reveals how (global) aspects of the distance map (that is, shape) can be "read out" locally, suggesting a solution to the border ownership problem. Since the reaction-diffusion equation defines a field, a possible information processing role for the local field potential can be defined. We argue that such fields also underlie the Gestalt notion of closure, especially when it is refined using modern experimental techniques. An important implication of this theoretical argument is that, if true, then network modeling must be extended to include the substrate surrounding spiking neurons, including glia.

The principle of coherence in multi-level brain information processing

Synchronisation has become one of the major scientific tools to explain biological order at many levels of organisation. In systems neuroscience, synchronised subthreshold and suprathreshold oscillatory neuronal activity within and between distributed neuronal assemblies is acknowledged as a fundamental mode of neuronal information processing. Coherent neuronal oscillations correlate with all basic cognitive functions, mediate local and long-range neuronal communication and affect synaptic plasticity. However, it remains unclear how the very fast and complex changes of functional neuronal connectivity necessary for cognition, as mediated by dynamic patterns of neuronal synchrony, could be explained exclusively based on the well-established synaptic mechanisms. A growing body of research indicates that the intraneuronal matrix, composed of cytoskeletal elements and their binding proteins, structurally and functionally connects the synapses within a neuron, modulates neurotransmission and memory consolidation, and is hypothesised to be involved in signal integration via electric signalling due to its charged surface. Theoretical modelling, as well as emerging experimental evidence indicate that neuronal cytoskeleton supports highly cooperative energy transport and information processing based on molecular coherence. We suggest that long-range coherent dynamics within the intra- and extracellular filamentous matrices could establish dynamic ordered states, capable of rapid modulations of functional neuronal connectivity via their interactions with neuronal membranes and synapses. Coherence may thus represent a common denominator of neurophysiological and biophysical approaches to brain information processing, operating at multiple levels of neuronal organisation, from which cognition may emerge as its cardinal manifestation.

Moving toward a generalizable application of central thalamic deep brain stimulation for support of forebrain arousal regulation in the severely injured brain

This review considers the challenges ahead for developing a generalizable strategy for the use of central thalamic deep brain stimulation (CT/DBS) to support arousal regulation mechanisms in the severely injured brain. Historical efforts to apply CT/DBS to patients with severe brain injuries and a proof-of-concept result from a single-subject study are discussed. Circuit and cellular mechanisms underlying the recovery of consciousness are considered for their relevance to the application of CT/DBS, to improve consciousness and cognition in nonprogressive brain injuries. Finally, directions for development, and testing of generalizable criteria for CT/DBS are suggested, which aim to identify neuronal substrates and behavioral profiles that may optimally benefit from support of arousal regulation mechanisms.

Location-dependent excitatory synaptic interactions in pyramidal neuron dendrites

Neocortical pyramidal neurons (PNs) receive thousands of excitatory synaptic contacts on their basal dendrites. Some act as classical driver inputs while others are thought to modulate PN responses based on sensory or behavioral context, but the biophysical mechanisms that mediate classical-contextual interactions in these dendrites remain poorly understood. We hypothesized that if two excitatory pathways bias their synaptic projections towards proximal vs. distal ends of the basal branches, the very different local spike thresholds and attenuation factors for inputs near and far from the soma might provide the basis for a classical-contextual functional asymmetry. Supporting this possibility, we found both in compartmental models and electrophysiological recordings in brain slices that the responses of basal dendrites to spatially separated inputs are indeed strongly asymmetric. Distal excitation lowers the local spike threshold for more proximal inputs, while having little effect on peak responses at the soma. In contrast, proximal excitation lowers the threshold, but also substantially increases the gain of distally-driven responses. Our findings support the view that PN basal dendrites possess significant analog computing capabilities, and suggest that the diverse forms of nonlinear response modulation seen in the neocortex, including uni-modal, cross-modal, and attentional effects, could depend in part on pathway-specific biases in the spatial distribution of excitatory synaptic contacts onto PN basal dendritic arbors.

Pyramidal neurons (PNs) are the principal neurons of the cerebral cortex and therefore lie at the heart of the brain's higher sensory, motor, affective, memory, and executive functions. But how do they work? In particular, how do they manage interactions between the classical “driver” inputs that give rise to their basic response properties, and “contextual” inputs that nonlinearly modulate those responses? It is known that PNs are contacted by thousands of excitatory synapses scattered about their dendrites, but despite decades of research, the “rules” that govern how inputs at different locations in the dendritic tree combine to influence the cell's firing rate remain poorly understood. We show here that two excitatory inputs contacting the same dendrite interact in an asymmetric nonlinear way that depends on their absolute and relative locations, where the resulting spectrum of location-dependent synaptic interactions constitutes a previously unknown form of spatial analog computation. In addition to suggesting a possible substrate for classical-contextual interactions in PN dendrites, our results imply that the computing functions of cortical circuits can only be fully understood when the detailed map of synaptic connectivity – the cortical connectome – is known down to the subdendritic level.