Synaptic interactions in neocortical local circuits: dual intracellular recordings in vitro

Adaptation-induced sharpening of orientation tuning curves in the mouse visual cortex

OBJECTIVE

Orientation selectivity is an emergent property of visual neurons across species with columnar and noncolumnar organization of the visual cortex. The emergence of orientation selectivity is more established in columnar cortical areas than in noncolumnar ones. Thus, how does orientation selectivity emerge in noncolumnar cortical areas after an adaptation protocol? Adaptation refers to the constant presentation of a nonoptimal stimulus (adapter) to a neuron under observation for a specific time. Previously, it had been shown that adaptation has varying effects on the tuning properties of neurons, such as orientation, spatial frequency, motion and so on.

BASIC METHODS

We recorded the mouse primary visual neurons (V1) at different orientations in the control (preadaptation) condition. This was followed by adapting neurons uninterruptedly for 12 min and then recording the same neurons postadaptation. An orientation selectivity index (OSI) for neurons was computed to compare them pre- and post-adaptation.

MAIN RESULTS

We show that 12-min adaptation increases the OSI of visual neurons ( n  = 113), that is, sharpens their tuning. Moreover, the OSI postadaptation increases linearly as a function of the OSI preadaptation.

CONCLUSION

The increased OSI postadaptation may result from a specific dendritic neural mechanism, potentially facilitating the rapid learning of novel features.

Measuring excitation-inhibition balance through spectral components of local field potentials

The balance between excitation and inhibition is critical to brain functioning, and dysregulation of this balance is a hallmark of numerous psychiatric conditions. Measuring this excitation-inhibition (E:I) balance in vivo has remained difficult, but theoretical models have proposed that characteristics of local field potentials (LFP) may provide an accurate proxy. To establish a conclusive link between LFP and E:I balance, we recorded single units and LFP from the prefrontal cortex (mPFC) of rats during decision making. Dynamic measures of synaptic coupling strength facilitated direct quantification of E:I balance and revealed a strong inverse relationship to broadband spectral power of LFP. These results provide a critical link between LFP and underlying network properties, opening the door for non-invasive recordings to measure E:I balance in clinical settings.

Processing of cell assemblies in the lateral entorhinal cortex

There is evidence that olfactory cortex responds to its afferent input with the generation of cell assemblies: collections of principal neurons that fire together over a time scale of tens of ms. If such assemblies form an odor representation, then a fundamental question is how each assembly then induces neuronal activity in downstream structures. We have addressed this question in a detailed model of superficial layers of lateral entorhinal cortex, a recipient of input from olfactory cortex and olfactory bulb. Our results predict that the response of the fan cell subpopulation can be approximated by a relatively simple Boolean process, somewhat along the lines of the McCulloch/Pitts scheme; this is the case because of the sparsity of recurrent excitation amongst fan cells. However, because of recurrent excitatory connections between layer 2 and layer 3 pyramidal cells, synaptic and probably also gap junctional, the response of pyramidal cell subnetworks cannot be so approximated. Because of the highly structured anatomy of entorhinal output projections, our model suggests that downstream targets of entorhinal cortex (dentate gyrus, hippocampal CA3, CA1, piriform cortex, olfactory bulb) receive differentially processed information.

Visualizing Oscillations in Brain Slices With Genetically Encoded Voltage Indicators

Genetically encoded voltage indicators (GEVIs) expressed pan-neuronally were able to optically resolve bicuculline induced spontaneous oscillations in brain slices of the mouse motor cortex. Three GEVIs were used that differ in their timing of response to voltage transients as well as in their voltage ranges. The duration, number of cycles, and frequency of the recorded oscillations reflected the characteristics of each GEVI used. Multiple oscillations imaged in the same slice never originated at the same location, indicating the lack of a “hot spot” for induction of the voltage changes. Comparison of pan-neuronal, Ca²⁺/calmodulin-dependent protein kinase II α restricted, and parvalbumin restricted GEVI expression revealed distinct profiles for the excitatory and inhibitory cells in the spontaneous oscillations of the motor cortex. Resolving voltage fluctuations across space, time, and cell types with GEVIs represent a powerful approach to dissecting neuronal circuit activity.

Distinct subtypes of inhibitory interneurons differentially promote the propagation of rate and temporal codes in the feedforward neural network

Sensory information is believed to be encoded in neuronal spikes using two different neural codes, the rate code (spike firing rate) and the temporal code (precisely-timed spikes). Since the sensory cortex has a highly hierarchical feedforward structure, sensory information-carrying neural codes should reliably propagate across the feedforward network (FFN) of the cortex. Experimental evidence suggests that inhibitory interneurons, such as the parvalbumin-positive (PV) and somatostatin-positive (SST) interneurons, that have distinctively different electrophysiological and synaptic properties, modulate the neural codes during sensory information processing in the cortex. However, how PV and SST interneurons impact on the neural code propagation in the cortical FFN is unknown. We address this question by building a five-layer FFN model consisting of a physiologically realistic Hodgkin-Huxley-type models of excitatory neurons and PV/SST interneurons at different ratios. In response to different firing rate inputs (20-80 Hz), a higher ratio of PV over SST interneurons promoted a reliable propagation of all ranges of firing rate inputs. In contrast, in response to a range of precisely-timed spikes in the form of pulse-packets [with a different number of spikes (α, 40-400 spikes) and degree of dispersion (σ, 0-20 ms)], a higher ratio of SST over PV interneurons promoted a reliable propagation of pulse-packets. Our simulation results show that PV and SST interneurons differentially promote a reliable propagation of the rate and temporal codes, respectively, indicating that the dynamic recruitment of PV and SST interneurons may play critical roles in a reliable propagation of sensory information-carrying neural codes in the cortical FFN.

Low-threshold spiking interneurons perform feedback inhibition in the lateral amygdala

Amygdala plays crucial roles in emotional learning. The lateral amygdala (LA) is the input station of the amygdala, where learning related plasticity occurs. The LA is cortical like in nature in terms of its cellular make up, composed of a majority of principal cells and a minority of interneurons with distinct subtypes defined by morphology, intrinsic electrophysiological properties and neurochemical expression profile. The specific functions served by LA interneuron subtypes remain elusive. This study aimed to elucidate the interneuron subtype mediating feedback inhibition. Electrophysiological evidence involving antidromic activation of recurrent LA circuitry via basolateral amygdala stimulation and paired recordings implicate low-threshold spiking interneurons in feedback inhibition. Recordings in somatostatin-cre animals crossed with tdtomato mice have revealed remarkable similarities between a subset of SOM+ interneurons and LTS interneurons. This study concludes that LTS interneurons, most of which are putatively SOM+, mediate feedback inhibition in the LA. Parallels with cortical areas and potential implications for information processing and plasticity are discussed.

Unveiling the Synaptic Function and Structure Using Paired Recordings From Synaptically Coupled Neurons

Synaptic transmission between neurons is the basic mechanism for information processing in cortical microcircuits. To date, paired recording from synaptically coupled neurons is the most widely used method which allows a detailed functional characterization of unitary synaptic transmission at the cellular and synaptic level in combination with a structural characterization of both pre- and postsynaptic neurons at the light and electron microscopic level. In this review, we will summarize the many applications of paired recordings to investigate synaptic function and structure. Paired recordings have been used to study the detailed electrophysiological and anatomical properties of synaptically coupled cell pairs within a synaptic microcircuit; this is critical in order to understand the connectivity rules and dynamic properties of synaptic transmission. Paired recordings can also be adopted for quantal analysis of an identified synaptic connection and to study the regulation of synaptic transmission by neuromodulators such as acetylcholine, the monoamines, neuropeptides, and adenosine etc. Taken together, paired recordings from synaptically coupled neurons will remain a very useful approach for a detailed characterization of synaptic transmission not only in the rodent brain but also that of other species including humans.

Early Sensory Loss Alters the Dendritic Branching and Spine Density of Supragranular Pyramidal Neurons in Rodent Primary Sensory Cortices

Multisensory integration in primary auditory (A1), visual (V1), and somatosensory cortex (S1) is substantially mediated by their direct interconnections and by thalamic inputs across the sensory modalities. We have previously shown in rodents (Mongolian gerbils) that during postnatal development, the anatomical and functional strengths of these crossmodal and also of sensory matched connections are determined by early auditory, somatosensory, and visual experience. Because supragranular layer III pyramidal neurons are major targets of corticocortical and thalamocortical connections, we investigated in this follow-up study how the loss of early sensory experience changes their dendritic morphology. Gerbils were sensory deprived early in development by either bilateral sciatic nerve transection at postnatal day (P) 5, ototoxic inner hair cell damage at P10, or eye enucleation at P10. Sholl and branch order analyses of Golgi-stained layer III pyramidal neurons at P28, which demarcates the end of the sensory critical period in this species, revealed that visual and somatosensory deprivation leads to a general increase of apical and basal dendritic branching in A1, V1, and S1. In contrast, dendritic branching, particularly of apical dendrites, decreased in all three areas following auditory deprivation. Generally, the number of spines, and consequently spine density, along the apical and basal dendrites decreased in both sensory deprived and non-deprived cortical areas. Therefore, we conclude that the loss of early sensory experience induces a refinement of corticocortical crossmodal and other cortical and thalamic connections by pruning of dendritic spines at the end of the critical period. Based on present and previous own results and on findings from the literature, we propose a scenario for multisensory development following early sensory loss.

Classifying dynamic transitions in high dimensional neural mass models: A random forest approach

Neural mass models (NMMs) are increasingly used to uncover the large-scale mechanisms of brain rhythms in health and disease. The dynamics of these models is dependent upon the choice of parameters, and therefore it is crucial to be able to understand how dynamics change when parameters are varied. Despite being considered low dimensional in comparison to micro-scale, neuronal network models, with regards to understanding the relationship between parameters and dynamics, NMMs are still prohibitively high dimensional for classical approaches such as numerical continuation. Therefore, we need alternative methods to characterise dynamics of NMMs in high dimensional parameter spaces. Here, we introduce a statistical framework that enables the efficient exploration of the relationship between model parameters and selected features of the simulated, emergent model dynamics of NMMs. We combine the classical machine learning approaches of trees and random forests to enable studying the effect that varying multiple parameters has on the dynamics of a model. The method proceeds by using simulations to transform the mathematical model into a database. This database is then used to partition parameter space with respect to dynamic features of interest, using random forests. This allows us to rapidly explore dynamics in high dimensional parameter space, capture the approximate location of qualitative transitions in dynamics and assess the relative importance of all parameters in the model in all dimensions simultaneously. We apply this method to a commonly used NMM in the context of transitions to seizure dynamics. We find that the inhibitory sub-system is most crucial for the generation of seizure dynamics, confirm and expand previous findings regarding the ratio of excitation and inhibition, and demonstrate that previously overlooked parameters can have a significant impact on model dynamics. We advocate the use of this method in future to constrain high dimensional parameter spaces enabling more efficient, person-specific, model calibration.

Spiking and Excitatory/Inhibitory Input Dynamics of Barrel Cells in Response to Whisker Deflections of Varying Velocity and Angular Direction

The spiking of barrel regular-spiking (RS) cells is tuned for both whisker deflection direction and velocity. Velocity tuning arises due to thalamocortical (TC) synchrony (but not spike quantity) varying with deflection velocity, coupled with feedforward inhibition, while direction selectivity is not fully understood, though may be due partly to direction tuning of TC spiking. Data show that as deflection direction deviates from the preferred direction of an RS cell, excitatory input to the RS cell diminishes minimally, but temporally shifts to coincide with the time-lagged inhibitory input. This work constructs a realistic large-scale model of a barrel; model RS cells exhibit velocity and direction selectivity due to TC input dynamics, with the experimentally observed sharpening of direction tuning with decreasing velocity. The model puts forth the novel proposal that RS→RS synapses can naturally and simply account for the unexplained direction dependence of RS cell inputs - as deflection direction deviates from the preferred direction of an RS cell, and TC input declines, RS→RS synaptic transmission buffers the decline in total excitatory input and causes a shift in timing of the excitatory input peak from the peak in TC input to the delayed peak in RS input. The model also provides several experimentally testable predictions on the velocity dependence of RS cell inputs. This model is the first, to my knowledge, to study the interaction of direction and velocity and propose physiological mechanisms for the stimulus dependence in the timing and amplitude of RS cell inputs.

Prominent facilitation at beta and gamma frequency range revealed with physiological calcium concentration in adult mouse piriform cortex in vitro

Neuronal activity is characterized by a diversity of oscillatory phenomena that are associated with multiple behavioral and cognitive processes, yet the functional consequences of these oscillations are not fully understood. Our aim was to determine whether and how these different oscillatory activities affect short-term synaptic plasticity (STP), using the olfactory system as a model. In response to odorant stimuli, the olfactory bulb displays a slow breathing rhythm as well as beta and gamma oscillations. Since the firing of olfactory bulb projecting neurons is phase-locked with beta and gamma oscillations, structures downstream from the olfactory bulb should be driven preferentially at these frequencies. We examined STP exhibited by olfactory bulb inputs in slices of adult mouse piriform cortex maintained in vitro in an in vivo-like ACSF (calcium concentration: 1.1 mM). We replaced the presynaptic neuronal firing rate by repeated electrical stimulation (frequency between 3.125 and 100 Hz) applied to the lateral olfactory tract. Our results revealed a considerable enhancement of postsynaptic response amplitude for stimulation frequencies in the beta and gamma range. A phenomenological model of STP fitted to the data suggests that the experimental results can be explained by the interplay between three mechanisms: a short-term facilitation mechanism (time constant ≈160 msec), and two short-term depression mechanisms (recovery time constants <20 msec and ≈140 msec). Increasing calcium concentration (2.2 mM) resulted in an increase in the time constant of facilitation and in a strengthening of the slowest depression mechanism. As a result, response enhancement was reduced and its peak shifted toward the low beta and alpha ranges while depression became predominant in the gamma band. Using environmental conditions corresponding to those that prevail in vivo, our study shows that STP in the lateral olfactory tract to layer Ia synapse allows amplification of olfactory bulb inputs at beta and gamma frequencies.

Spontaneous dynamics of neural networks in deep layers of prefrontal cortex

Cortical systems maintain and process information through the sustained activation of recurrent local networks of neurons. Layer 5 is known to have a major role in generating the recurrent activation associated with these functions, but relatively little is known about its intrinsic dynamics at the mesoscopic level of large numbers of neighboring neurons. Using calcium imaging, we measured the spontaneous activity of networks of deep-layer medial prefrontal cortical neurons in an acute slice model. Inferring the simultaneous activity of tens of neighboring neurons, we found that while the majority showed only sporadic activity, a subset of neurons engaged in sustained delta frequency rhythmic activity. Spontaneous activity under baseline conditions was weakly correlated between pairs of neurons, and rhythmic neurons showed little coherence in their oscillations. However, we consistently observed brief bouts of highly synchronous activity that must be attributed to network activity. NMDA-mediated stimulation enhanced rhythmicity, synchrony, and correlation within these local networks. These results characterize spontaneous prefrontal activity at a previously unexplored spatiotemporal scale and suggest that medial prefrontal cortex can act as an intrinsic generator of delta oscillations.NEW & NOTEWORTHY Using calcium imaging and a novel analytic framework, we characterized the spontaneous and NMDA-evoked activity of layer 5 prefrontal cortex at a largely unexplored spatiotemporal scale. Our results suggest that the mPFC microcircuitry is capable of intrinsically generating delta oscillations and sustaining synchronized network activity that is potentially relevant for understanding its contribution to cognitive processes.

Somatostatin-Expressing Inhibitory Interneurons in Cortical Circuits

Cortical inhibitory neurons exhibit remarkable diversity in their morphology, connectivity, and synaptic properties. Here, we review the function of somatostatin-expressing (SOM) inhibitory interneurons, focusing largely on sensory cortex. SOM neurons also comprise a number of subpopulations that can be distinguished by their morphology, input and output connectivity, laminar location, firing properties, and expression of molecular markers. Several of these classes of SOM neurons show unique dynamics and characteristics, such as facilitating synapses, specific axonal projections, intralaminar input, and top-down modulation, which suggest possible computational roles. SOM cells can be differentially modulated by behavioral state depending on their class, sensory system, and behavioral paradigm. The functional effects of such modulation have been studied with optogenetic manipulation of SOM cells, which produces effects on learning and memory, task performance, and the integration of cortical activity. Different classes of SOM cells participate in distinct disinhibitory circuits with different inhibitory partners and in different cortical layers. Through these disinhibitory circuits, SOM cells help encode the behavioral relevance of sensory stimuli by regulating the activity of cortical neurons based on subcortical and intracortical modulatory input. Associative learning leads to long-term changes in the strength of connectivity of SOM cells with other neurons, often influencing the strength of inhibitory input they receive. Thus despite their heterogeneity and variability across cortical areas, current evidence shows that SOM neurons perform unique neural computations, forming not only distinct molecular but also functional subclasses of cortical inhibitory interneurons.

Inhibition in the Human Auditory Cortex

Despite their indispensable roles in sensory processing, little is known about inhibitory interneurons in humans. Inhibitory postsynaptic potentials cannot be recorded non-invasively, at least in a pure form, in humans. We herein sought to clarify whether prepulse inhibition (PPI) in the auditory cortex reflected inhibition via interneurons using magnetoencephalography. An abrupt increase in sound pressure by 10 dB in a continuous sound was used to evoke the test response, and PPI was observed by inserting a weak (5 dB increase for 1 ms) prepulse. The time course of the inhibition evaluated by prepulses presented at 10-800 ms before the test stimulus showed at least two temporally distinct inhibitions peaking at approximately 20-60 and 600 ms that presumably reflected IPSPs by fast spiking, parvalbumin-positive cells and somatostatin-positive, Martinotti cells, respectively. In another experiment, we confirmed that the degree of the inhibition depended on the strength of the prepulse, but not on the amplitude of the prepulse-evoked cortical response, indicating that the prepulse-evoked excitatory response and prepulse-evoked inhibition reflected activation in two different pathways. Although many diseases such as schizophrenia may involve deficits in the inhibitory system, we do not have appropriate methods to evaluate them; therefore, the easy and non-invasive method described herein may be clinically useful.

Optical detection of neuron connectivity by random access two-photon microscopy

BACKGROUND

Knowledge about the distribution, strength, and direction of synaptic connections within neuronal networks are crucial for understanding brain function. Electrophysiology using multiple electrodes provides a very high temporal resolution, but does not yield sufficient spatial information for resolving neuronal connection topology. Optical recording techniques using single-cell resolution have provided promise for providing spatial information. Although calcium imaging from hundreds of neurons has provided a novel view of the neural connections within the network, the kinetics of calcium responses are not fast enough to resolve each action potential event with high fidelity. Therefore, it is not possible to detect the direction of neuronal connections.

NEW METHOD

We took advantage of the fast kinetics and large dynamic range of the DiO/DPA combination of voltage sensitive dye and the fast scan speed of a custom-made random-access two-photon microscope to resolve each action potential event from multiple neurons in culture.

RESULTS

Long-duration recording up to 100min from cultured hippocampal neurons yielded sufficient numbers of spike events for analyzing synaptic connections. Cross-correlation analysis of neuron pairs clearly distinguished synaptically connected neuron pairs with the connection direction.

COMPARISON WITH EXISTING METHOD

The long duration recording of action potentials with voltage-sensitive dye utilized in the present study is much longer than in previous studies. Simultaneous optical voltage and calcium measurements revealed that voltage-sensitive dye is able to detect firing events more reliably than calcium indicators.

CONCLUSIONS

This novel method reveals a new view of the functional structure of neuronal networks.

Unilateral and Bilateral Cortical Resection: Effects on Spike-Wave Discharges in a Genetic Absence Epilepsy Model

Research Question

Recent discoveries have challenged the traditional view that the thalamus is the primary source driving spike-and-wave discharges (SWDs). At odds, SWDs in genetic absence models have a cortical focal origin in the deep layers of the perioral region of the somatosensory cortex. The present study examines the effect of unilateral and bilateral surgical resection of the assumed focal cortical region on the occurrence of SWDs in anesthetized WAG/Rij rats, a well described and validated genetic absence model.

Methods

Male WAG/Rij rats were used: 9 in the resected and 6 in the control group. EEG recordings were made before and after craniectomy, after unilateral and after bilateral removal of the focal region.

Results

SWDs decreased after unilateral cortical resection, while SWDs were no longer noticed after bilateral resection. This was also the case when the resected areas were restricted to layers I-IV with layers V and VI intact.

Conclusions

These results suggest that SWDs are completely abolished after bilateral removal of the focal region, most likely by interference with an intracortical columnar circuit. The evidence suggests that absence epilepsy is a network type of epilepsy since interference with only the local cortical network abolishes all seizures.

Anatomy and physiology of the thick-tufted layer 5 pyramidal neuron

The thick-tufted layer 5 (TTL5) pyramidal neuron is one of the most extensively studied neuron types in the mammalian neocortex and has become a benchmark for understanding information processing in excitatory neurons. By virtue of having the widest local axonal and dendritic arborization, the TTL5 neuron encompasses various local neocortical neurons and thereby defines the dimensions of neocortical microcircuitry. The TTL5 neuron integrates input across all neocortical layers and is the principal output pathway funneling information flow to subcortical structures. Several studies over the past decades have investigated the anatomy, physiology, synaptology, and pathophysiology of the TTL5 neuron. This review summarizes key discoveries and identifies potential avenues of research to facilitate an integrated and unifying understanding on the role of a central neuron in the neocortex.

Spectral and Temporal Acoustic Features Modulate Response Irregularities within Primary Auditory Cortex Columns

Assemblies of vertically connected neurons in the cerebral cortex form information processing units (columns) that participate in the distribution and segregation of sensory signals. Despite well-accepted models of columnar architecture, functional mechanisms of inter-laminar communication remain poorly understood. Hence, the purpose of the present investigation was to examine the effects of sensory information features on columnar response properties. Using acute recording techniques, extracellular response activity was collected from the right hemisphere of eight mature cats (felis catus). Recordings were conducted with multichannel electrodes that permitted the simultaneous acquisition of neuronal activity within primary auditory cortex columns. Neuronal responses to simple (pure tones), complex (noise burst and frequency modulated sweeps), and ecologically relevant (con-specific vocalizations) acoustic signals were measured. Collectively, the present investigation demonstrates that despite consistencies in neuronal tuning (characteristic frequency), irregularities in discharge activity between neurons of individual A1 columns increase as a function of spectral (signal complexity) and temporal (duration) acoustic variations.

Impaired adrenergic-mediated plasticity of prefrontal cortical glutamate synapses in rats with developmental disruption of the ventral hippocampus

Neonatal ventral hippocampus (nVH) lesion in rats is a useful model to study developmental origins of adult cognitive deficits and certain features of schizophrenia. nVH lesion-induced reorganization of excitatory and inhibitory neurotransmissions within prefrontal cortical (PFC) circuits is widely believed to be responsible for many of the behavioral abnormalities in these animals. Here we provide evidence that development of an aberrant medial PFC (mPFC) α-1 adrenergic receptor (α-1AR) function following neonatal lesion markedly affects glutamatergic synaptic plasticity within PFC microcircuits and contributes to PFC-related behavior abnormalities. Using whole-cell patch-clamp recording, we report that norepinephrine-induced α-1AR-dependent long-term depression (LTD) in a subset of cortico-cortical glutamatergic inputs is strikingly diminished in mPFC slices from nVH-lesioned rats. The LTD impairment occurs in conjunction with completely blunted α-1AR signaling through extracellular signal-regulated kinase 1/2. These α-1AR abnormalities have functional significance in a mPFC-related function, that is, extinction of conditioned fear memory. Post-pubertal animals with nVH lesion show significant resistance to extinction of fear by repeated presentations of the conditioned tone stimulus. mPFC infusion of an α-1AR antagonist (benoxathian) or LTD blocking peptide (Tat-GluR23Y) impaired fear extinction in sham controls, but had no significant effect in the lesioned animals. The data suggest that impaired α-1 adrenergic regulation of cortical glutamatergic synaptic plasticity may be an important mechanism in cognitive dysfunctions reported in neurodevelopmental psychiatric disorders.

3D clustering of GABAergic neurons enhances inhibitory actions on excitatory neurons in the mouse visual cortex

Neocortical neurons with similar functional properties assemble into spatially coherent circuits, but it remains unclear how inhibitory interneurons are organized. We applied in vivo two-photon functional Ca(2+) imaging and whole-cell recording of synaptic currents to record visual responses of cortical neurons and analyzed their spatial arrangements. GABAergic interneurons were clustered in the 3D space of the mouse visual cortex, and excitatory neurons located within the clusters (insiders) had a lower amplitude and sharper orientation tuning of visual responses than outsiders. Inhibitory synaptic currents recorded from the insiders were larger than those of the outsiders. Single, isolated interneurons did not show such a location-tuning/amplitude relationship. The two principal subtypes of interneurons, parvalbumin- and somatostatin-expressing neurons, also formed clusters with only slightly overlapping each other and exhibited a different location-tuning relationship. These findings suggest that GABAergic interneurons and their subgroups form clusters to make their inhibitory function more effective than isolated interneurons.

Slicing, sampling, and distance-dependent effects affect network measures in simulated cortical circuit structures

The neuroanatomical connectivity of cortical circuits is believed to follow certain rules, the exact origins of which are still poorly understood. In particular, numerous nonrandom features, such as common neighbor clustering, overrepresentation of reciprocal connectivity, and overrepresentation of certain triadic graph motifs have been experimentally observed in cortical slice data. Some of these data, particularly regarding bidirectional connectivity are seemingly contradictory, and the reasons for this are unclear. Here we present a simple static geometric network model with distance-dependent connectivity on a realistic scale that naturally gives rise to certain elements of these observed behaviors, and may provide plausible explanations for some of the conflicting findings. Specifically, investigation of the model shows that experimentally measured nonrandom effects, especially bidirectional connectivity, may depend sensitively on experimental parameters such as slice thickness and sampling area, suggesting potential explanations for the seemingly conflicting experimental results.

Long-term recordings improve the detection of weak excitatory-excitatory connections in rat prefrontal cortex

Characterization of synaptic connectivity is essential to understanding neural circuit dynamics. For extracellularly recorded spike trains, indirect evidence for connectivity can be inferred from short-latency peaks in the correlogram between two neurons. Despite their predominance in cortex, however, significant interactions between excitatory neurons (E) have been hard to detect because of their intrinsic weakness. By taking advantage of long duration recordings, up to 25 h, from rat prefrontal cortex, we found that 7.6% of the recorded pyramidal neurons are connected. This corresponds to ∼70% of the local E-E connection probability that has been reported by paired intracellular recordings (11.6%). This value is significantly higher than previous reports from extracellular recordings, but still a substantial underestimate. Our analysis showed that long recording times and strict significance thresholds are necessary to detect weak connections while avoiding false-positive results, but will likely still leave many excitatory connections undetected. In addition, we found that hyper-reciprocity of connections in prefrontal cortex that was shown previously by paired intracellular recordings was only present in short-distance, but not in long distance (∼300 micrometers or more) interactions. As hyper-reciprocity is restricted to local clusters, it might be a minicolumnar effect. Given the current surge of interest in very high-density neural spike recording (e.g., NIH BRAIN Project) it is of paramount importance that we have statistically reliable methods for estimating connectivity from cross-correlation analysis available. We provide an important step in this direction.

SIMULATING VERTICAL AND HORIZONTAL INHIBITION WITH SHORT-TERM DYNAMICS IN A MULTI-COLUMN MULTI-LAYER MODEL OF NEOCORTEX

The paper introduces a multi-layer multi-column model of the cortex that uses four different neuron types and short-term plasticity dynamics. It was designed with details of neuronal connectivity available in the literature and meets these conditions: (1) biologically accurate laminar and columnar flows of activity, (2) normal function of low-threshold spiking and fast spiking neurons, and (3) ability to generate different stages of epileptiform activity. With these characteristics the model allows for modeling lesioned or malformed cortex, i.e. examine properties of developmentally malformed cortex in which the balance between inhibitory neuron subtypes is disturbed.

Early hypersynchrony in juvenile PINK1(-)/(-) motor cortex is rescued by antidromic stimulation

In Parkinson’s disease (PD), cortical networks show enhanced synchronized activity but whether this precedes motor signs is unknown. We investigated this question in PINK1⁻/⁻ mice, a genetic rodent model of the PARK6 variant of familial PD which shows impaired spontaneous locomotion at 16 months. We used two-photon calcium imaging and whole-cell patch clamp in slices from juvenile (P14–P21) wild-type or PINK1⁻/⁻ mice. We designed a horizontal tilted cortico-subthalamic slice where the only connection between cortex and subthalamic nucleus (STN) is the hyperdirect cortico-subthalamic pathway. We report excessive correlation and synchronization in PINK1⁻/⁻ M1 cortical networks 15 months before motor impairment. The percentage of correlated pairs of neurons and their strength of correlation were higher in the PINK1⁻/⁻ M1 than in the wild type network and the synchronized network events involved a higher percentage of neurons. Both features were independent of thalamo-cortical pathways, insensitive to chronic levodopa treatment of pups, but totally reversed by antidromic invasion of M1 pyramidal neurons by axonal spikes evoked by high frequency stimulation (HFS) of the STN. Our study describes an early excess of synchronization in the PINK1⁻/⁻ cortex and suggests a potential role of antidromic activation of cortical interneurons in network desynchronization. Such backward effect on interneurons activity may be of importance for HFS-induced network desynchronization.

Specialized prefrontal "auditory fields": organization of primate prefrontal-temporal pathways

No other modality is more frequently represented in the prefrontal cortex than the auditory, but the role of auditory information in prefrontal functions is not well understood. Pathways from auditory association cortices reach distinct sites in the lateral, orbital, and medial surfaces of the prefrontal cortex in rhesus monkeys. Among prefrontal areas, frontopolar area 10 has the densest interconnections with auditory association areas, spanning a large antero-posterior extent of the superior temporal gyrus from the temporal pole to auditory parabelt and belt regions. Moreover, auditory pathways make up the largest component of the extrinsic connections of area 10, suggesting a special relationship with the auditory modality. Here we review anatomic evidence showing that frontopolar area 10 is indeed the main frontal “auditory field” as the major recipient of auditory input in the frontal lobe and chief source of output to auditory cortices. Area 10 is thought to be the functional node for the most complex cognitive tasks of multitasking and keeping track of information for future decisions. These patterns suggest that the auditory association links of area 10 are critical for complex cognition. The first part of this review focuses on the organization of prefrontal-auditory pathways at the level of the system and the synapse, with a particular emphasis on area 10. Then we explore ideas on how the elusive role of area 10 in complex cognition may be related to the specialized relationship with auditory association cortices.

Modulatory effects of inhibition on persistent activity in a cortical microcircuit model

Neocortical network activity is generated through a dynamic balance between excitation, provided by pyramidal neurons, and inhibition, provided by interneurons. Imbalance of the excitation/inhibition ratio has been identified in several neuropsychiatric diseases, such as schizophrenia, autism and epilepsy, which also present with other cognitive deficits and symptoms associated with prefrontal cortical (PFC) dysfunction. We undertook a computational approach to study how changes in the excitation/inhibition balance in a PFC microcircuit model affect the properties of persistent activity, considered the cellular correlate of working memory function in PFC. To this end, we constructed a PFC microcircuit, consisting of pyramidal neuron models and all three different interneuron types: fast-spiking (FS), regular-spiking (RS), and irregular-spiking (IS) interneurons. Persistent activity was induced in the microcircuit model with a stimulus to the proximal apical dendrites of the pyramidal neuron models, and its properties were analyzed, such as the induction profile, the interspike intervals (ISIs) and neuronal synchronicity. Our simulations showed that (a) the induction but not the firing frequency or neuronal synchronicity is modulated by changes in the NMDA-to-AMPA ratio on FS interneuron model, (b) removing or decreasing the FS model input to the pyramidal neuron models greatly limited the biophysical modulation of persistent activity induction, decreased the ISIs and neuronal synchronicity during persistent activity, (c) the induction and firing properties could not be altered by the addition of other inhibitory inputs to the soma (from RS or IS models), and (d) the synchronicity change could be reversed by the addition of other inhibitory inputs to the soma, but beyond the levels of the control network. Thus, generic somatic inhibition acts as a pacemaker of persistent activity and FS specific inhibition modulates the output of the pacemaker.

Simulating lesions in multi-layer, multi-columnar model of neocortex

The paper presents results of modeling global and focal loss of layers in a multi-columnar model of neocortex. Specifically, the spread of activity across columns in conditions of inhibitory blockade is compared. With very low inhibition activity spreads through all layers, however, deep layers are critical for spread of activity when inhibition is only moderately blocked.

Altered neural connectivity in excitatory and inhibitory cortical circuits in autism

Converging evidence from diverse studies suggests that atypical brain connectivity in autism affects in distinct ways short- and long-range cortical pathways, disrupting neural communication and the balance of excitation and inhibition. This hypothesis is based mostly on functional non-invasive studies that show atypical synchronization and connectivity patterns between cortical areas in children and adults with autism. Indirect methods to study the course and integrity of major brain pathways at low resolution show changes in fractional anisotropy (FA) or diffusivity of the white matter in autism. Findings in post-mortem brains of adults with autism provide evidence of changes in the fine structure of axons below prefrontal cortices, which communicate over short- or long-range pathways with other cortices and subcortical structures. Here we focus on evidence of cellular and axon features that likely underlie the changes in short- and long-range communication in autism. We review recent findings of changes in the shape, thickness, and volume of brain areas, cytoarchitecture, neuronal morphology, cellular elements, and structural and neurochemical features of individual axons in the white matter, where pathology is evident even in gross images. We relate cellular and molecular features to imaging and genetic studies that highlight a variety of polymorphisms and epigenetic factors that primarily affect neurite growth and synapse formation and function in autism. We report preliminary findings of changes in autism in the ratio of distinct types of inhibitory neurons in prefrontal cortex, known to shape network dynamics and the balance of excitation and inhibition. Finally we present a model that synthesizes diverse findings by relating them to developmental events, with a goal to identify common processes that perturb development in autism and affect neural communication, reflected in altered patterns of attention, social interactions, and language.

No consistent relationship between gamma power and peak frequency in macaque primary visual cortex

Neural activity in the gamma frequency range ("gamma") is elevated during active cognitive states. Gamma has been proposed to play an important role in cortical function, although this is debated. Understanding what function gamma might fulfill requires a better understanding of its properties and the mechanisms that generate it. Gamma is characterized by its spectral power and peak frequency, and variations in both parameters have been associated with changes in behavioral performance. Modeling studies suggest these properties are co-modulated, but this has not been established. To test the relationship between these properties, we measured local field potentials (LFPs) and neuronal spiking responses in primary visual cortex of anesthetized monkeys, for drifting sinusoidal gratings of different sizes, contrasts, orientations and masked with different levels of noise. We find that there is no fixed relationship between LFP gamma power and peak frequency, and neither is related to the strength of spiking activity. We propose a simple model that can account for the complex stimulus dependence we observe, and suggest that separate mechanisms determine gamma power and peak frequency.

Reduced gamma frequency in the medial frontal cortex of aged rats during behavior and rest: implications for age-related behavioral slowing

Age-related cognitive and behavioral slowing may be caused by changes in the speed of neural signaling or by changes in the number of signaling steps necessary to achieve a given function. In the mammalian cortex, neural communication is organized by a 30-100 Hz "gamma" oscillation. There is a putative link between the gamma frequency and the speed of processing in a neural network: the dynamics of pyramidal neuron membrane time constants suggest that synaptic integration is framed by the gamma cycle, and pharmacological slowing of gamma also slows reaction times on behavioral tasks. The present experiments identify reductions in a robust 40-70 Hz gamma oscillation in the aged rat medial frontal cortex. The reductions were observed in the form of local field potentials, later peaks in fast-spiking neuron autocorrelations, and delays in the spiking of inhibitory neurons following local excitatory signals. Gamma frequency did not vary with movement speed, but rats with slower gamma also moved more slowly. Gamma frequency age differences were not observed in hippocampus. Hippocampal CA1 fast-spiking neurons exhibited interspike intervals consistent with a fast (70-100 Hz) gamma frequency, a pattern maintained across theta phases and theta frequencies independent of fluctuations in the average firing rates of the neurons. We propose that an average lengthening of the cortical 15-25 ms gamma cycle is one factor contributing to age-related slowing and that future attempts to offset cognitive declines will find a target in the response of fast-spiking inhibitory neurons to excitatory inputs.

The cell-type specific cortical microcircuit: relating structure and activity in a full-scale spiking network model

In the past decade, the cell-type specific connectivity and activity of local cortical networks have been characterized experimentally to some detail. In parallel, modeling has been established as a tool to relate network structure to activity dynamics. While available comprehensive connectivity maps ( Thomson, West, et al. 2002; Binzegger et al. 2004) have been used in various computational studies, prominent features of the simulated activity such as the spontaneous firing rates do not match the experimental findings. Here, we analyze the properties of these maps to compile an integrated connectivity map, which additionally incorporates insights on the specific selection of target types. Based on this integrated map, we build a full-scale spiking network model of the local cortical microcircuit. The simulated spontaneous activity is asynchronous irregular and cell-type specific firing rates are in agreement with in vivo recordings in awake animals, including the low rate of layer 2/3 excitatory cells. The interplay of excitation and inhibition captures the flow of activity through cortical layers after transient thalamic stimulation. In conclusion, the integration of a large body of the available connectivity data enables us to expose the dynamical consequences of the cortical microcircuitry.

Principles governing the operation of synaptic inhibition in dendrites

Synaptic inhibition plays a key role in shaping the dynamics of neuronal networks and selecting cell assemblies. Typically, an inhibitory axon contacts a particular dendritic subdomain of its target neuron, where it often makes 10-20 synapses, sometimes on very distal branches. The functional implications of such a connectivity pattern are not well understood. Our experimentally based theoretical study highlights several new and counterintuitive principles for dendritic inhibition. We show that distal "off-path" rather than proximal "on-path" inhibition effectively dampens proximal excitable dendritic "hotspots," thus powerfully controlling the neuron's output. Additionally, with multiple synaptic contacts, inhibition operates globally, spreading centripetally hundreds of micrometers from the inhibitory synapses. Consequently, inhibition in regions lacking inhibitory synapses may exceed that at the synaptic sites themselves. These results offer new insights into the synergetic effect of dendritic inhibition in controlling dendritic excitability and plasticity and in dynamically molding functional dendritic subdomains and their output.

Statistical connectivity provides a sufficient foundation for specific functional connectivity in neocortical neural microcircuits

It is well-established that synapse formation involves highly selective chemospecific mechanisms, but how neuron arbors are positioned before synapse formation remains unclear. Using 3D reconstructions of 298 neocortical cells of different types (including nest basket, small basket, large basket, bitufted, pyramidal, and Martinotti cells), we constructed a structural model of a cortical microcircuit, in which cells of different types were independently and randomly placed. We compared the positions of physical appositions resulting from the incidental overlap of axonal and dendritic arbors in the model (statistical structural connectivity) with the positions of putative functional synapses (functional synaptic connectivity) in 90 synaptic connections reconstructed from cortical slice preparations. Overall, we found that statistical connectivity predicted an average of 74 ± 2.7% (mean ± SEM) synapse location distributions for nine types of cortical connections. This finding suggests that chemospecific attractive and repulsive mechanisms generally do not result in pairwise-specific connectivity. In some cases, however, the predicted distributions do not match precisely, indicating that chemospecific steering and aligning of the arbors may occur for some types of connections. This finding suggests that random alignment of axonal and dendritic arbors provides a sufficient foundation for specific functional connectivity to emerge in local neural microcircuits.

Multiple cognitive abilities from a single cortical algorithm

One strong claim made by the representational-hierarchical account of cortical function in the ventral visual stream (VVS) is that the VVS is a functional continuum: the basic computations carried out in service of a given cognitive function, such as recognition memory or visual discrimination, might be the same at all points along the VVS. Here, we use a single-layer computational model with a fixed learning mechanism and set of parameters to simulate a variety of cognitive phenomena from different parts of the functional continuum of the VVS: recognition memory, categorization of perceptually related stimuli, perceptual learning of highly similar stimuli, and development of retinotopy and orientation selectivity. The simulation results indicate--consistent with the representational-hierarchical view--that the simple existence of different levels of representational complexity in different parts of the VVS is sufficient to drive the emergence of distinct regions that appear to be specialized for solving a particular task, when a common neurocomputational learning algorithm is assumed across all regions. Thus, our data suggest that it is not necessary to invoke computational differences to understand how different cortical regions can appear to be specialized for what are considered to be very different psychological functions.

Activity-dependent energy budget for neocortical signaling: effect of short-term synaptic plasticity on the energy expended by spiking and synaptic activity

The available estimate of the energy expended for signaling in rat neocortex is refined to examine the separate contribution of spiking and synaptic activity as a function of average neuronal firing rate. By taking into account a phenomenological model of short-term synaptic plasticity, we show that the transition from low to high cortical activity is accompanied by a substantial increase in relative energy consumed by action potentials vs. synaptic potentials. This consideration might be important for a deeper understanding of how information is represented in the cortex and which metabolic pathways are upregulated to sustain cortical activity.

Columnar interactions determine horizontal propagation of recurrent network activity in neocortex

The cortex is organized in vertical and horizontal circuits that determine the spatiotemporal properties of distributed cortical activity. Despite detailed knowledge of synaptic interactions among individual cells in the neocortex, little is known about the rules governing interactions among local populations. Here, we used self-sustained recurrent activity generated in cortex, also known as up-states, in rat thalamocortical slices in vitro to understand interactions among laminar and horizontal circuits. By means of intracellular recordings and fast optical imaging with voltage-sensitive dyes, we show that single thalamic inputs activate the cortical column in a preferential layer 4 (L4) → layer 2/3 (L2/3) → layer 5 (L5) sequence, followed by horizontal propagation with a leading front in supragranular and infragranular layers. To understand the laminar and columnar interactions, we used focal injections of TTX to block activity in small local populations, while preserving functional connectivity in the rest of the network. We show that L2/3 alone, without underlying L5, does not generate self-sustained activity and is inefficient propagating activity horizontally. In contrast, L5 sustains activity in the absence of L2/3 and is necessary and sufficient to propagate activity horizontally. However, loss of L2/3 delays horizontal propagation via L5. Finally, L5 amplifies activity in L2/3. Our results show for the first time that columnar interactions between supragranular and infragranular layers are required for the normal propagation of activity in the neocortex. Our data suggest that supragranular and infragranular circuits, with their specific and complex set of inputs and outputs, work in tandem to determine the patterns of cortical activation observed in vivo.

Preferential electrical coupling regulates neocortical lineage-dependent microcircuit assembly

Radial glial cells are the primary neural progenitor cells in the developing neocortex. Consecutive asymmetric divisions of individual radial glial progenitor cells produce a number of sister excitatory neurons that migrate along the elongated radial glial fibre, resulting in the formation of ontogenetic columns. Moreover, sister excitatory neurons in ontogenetic columns preferentially develop specific chemical synapses with each other rather than with nearby non-siblings. Although these findings provide crucial insight into the emergence of functional columns in the neocortex, little is known about the basis of this lineage-dependent assembly of excitatory neuron microcircuits at single-cell resolution. Here we show that transient electrical coupling between radially aligned sister excitatory neurons regulates the subsequent formation of specific chemical synapses in the neocortex. Multiple-electrode whole-cell recordings showed that sister excitatory neurons preferentially form strong electrical coupling with each other rather than with adjacent non-sister excitatory neurons during early postnatal stages. This preferential coupling allows selective electrical communication between sister excitatory neurons, promoting their action potential generation and synchronous firing. Interestingly, although this electrical communication largely disappears before the appearance of chemical synapses, blockade of the electrical communication impairs the subsequent formation of specific chemical synapses between sister excitatory neurons in ontogenetic columns. These results suggest a strong link between lineage-dependent transient electrical coupling and the assembly of precise excitatory neuron microcircuits in the neocortex.

Contrast-dependent variations in the excitatory classical receptive field and suppressive nonclassical receptive field of cat primary visual cortex

In area V1 of cat and monkey, there is a surround region beyond the classical receptive field (CRF) which alone is unresponsive but may modulate the cell's response. This field is referred to as the "nonclassical receptive field" (nCRF). It has been reported in monkey that the extent of CRF and/or nCRF of V1 neurons is not fixed but varies with stimulus contrast. We reexamined the contrast dependence of V1 neurons in cat to determine whether this differs from previous studies in macaque. By fitting the spatial summation curves obtained at different contrasts with a difference of Gaussians model, we estimated quantitatively the effect of contrast on the spatial extent of the CRF and nCRF as well as the strength of surround suppression. Our results showed that both the CRF and nCRF expanded at low contrast, but the expansion is more marked for the CRF than for the nCRF. Although the effect of contrast on surround suppression was varied, the overall suppression increased significantly at high contrast. Moreover, the contrast-dependent change in the extent of CRF is independent of the change in suppression strength. Overall, our results in cat are in agreement with those obtained in macaque money.

Membrane properties and the balance between excitation and inhibition control gamma-frequency oscillations arising from feedback inhibition

Computational studies as well as in vivo and in vitro results have shown that many cortical neurons fire in a highly irregular manner and at low average firing rates. These patterns seem to persist even when highly rhythmic signals are recorded by local field potential electrodes or other methods that quantify the summed behavior of a local population. Models of the 30-80 Hz gamma rhythm in which network oscillations arise through 'stochastic synchrony' capture the variability observed in the spike output of single cells while preserving network-level organization. We extend upon these results by constructing model networks constrained by experimental measurements and using them to probe the effect of biophysical parameters on network-level activity. We find in simulations that gamma-frequency oscillations are enabled by a high level of incoherent synaptic conductance input, similar to the barrage of noisy synaptic input that cortical neurons have been shown to receive in vivo. This incoherent synaptic input increases the emergent network frequency by shortening the time scale of the membrane in excitatory neurons and by reducing the temporal separation between excitation and inhibition due to decreased spike latency in inhibitory neurons. These mechanisms are demonstrated in simulations and in vitro current-clamp and dynamic-clamp experiments. Simulation results further indicate that the membrane potential noise amplitude has a large impact on network frequency and that the balance between excitatory and inhibitory currents controls network stability and sensitivity to external inputs.

Cognitive consilience: primate non-primary neuroanatomical circuits underlying cognition

Interactions between the cerebral cortex, thalamus, and basal ganglia form the basis of cognitive information processing in the mammalian brain. Understanding the principles of neuroanatomical organization in these structures is critical to understanding the functions they perform and ultimately how the human brain works. We have manually distilled and synthesized hundreds of primate neuroanatomy facts into a single interactive visualization. The resulting picture represents the fundamental neuroanatomical blueprint upon which cognitive functions must be implemented. Within this framework we hypothesize and detail 7 functional circuits corresponding to psychological perspectives on the brain: consolidated long-term declarative memory, short-term declarative memory, working memory/information processing, behavioral memory selection, behavioral memory output, cognitive control, and cortical information flow regulation. Each circuit is described in terms of distinguishable neuronal groups including the cerebral isocortex (9 pyramidal neuronal groups), parahippocampal gyrus and hippocampus, thalamus (4 neuronal groups), basal ganglia (7 neuronal groups), metencephalon, basal forebrain, and other subcortical nuclei. We focus on neuroanatomy related to primate non-primary cortical systems to elucidate the basis underlying the distinct homotypical cognitive architecture. To display the breadth of this review, we introduce a novel method of integrating and presenting data in multiple independent visualizations: an interactive website (http://www.frontiersin.org/files/cognitiveconsilience/index.html) and standalone iPhone and iPad applications. With these tools we present a unique, annotated view of neuroanatomical consilience (integration of knowledge).

Specificity and randomness: structure-function relationships in neural circuits

A fundamental but unsolved problem in neuroscience is how connections between neurons might underlie information processing in central circuits. Building wiring diagrams of neural networks may accelerate our understanding of how they compute. But even if we had wiring diagrams, it is critical to know what neurons in a circuit are doing: their physiology. In both the retina and cerebral cortex, a great deal is known about topographic specificity, such as lamination and cell-type specificity of connections. Little, however, is known about connections as they relate to function. Here, we review how advances in functional imaging and electron microscopy have recently allowed the examination of relationships between sensory physiology and synaptic connections in cortical and retinal circuits.

A spatially extended model for macroscopic spike-wave discharges

Spike-wave discharges are a distinctive feature of epileptic seizures. So far, they have not been reported in spatially extended neural field models. We study a space-independent version of the Amari neural field model with two competing inhibitory populations. We show that this competition leads to robust spike-wave dynamics if the inhibitory populations operate on different time-scales. The spike-wave oscillations present a fold/homoclinic type bursting. From this result we predict parameters of the extended Amari system where spike-wave oscillations produce a spatially homogeneous pattern. We propose this mechanism as a prototype of macroscopic epileptic spike-wave discharges. To our knowledge this is the first example of robust spike-wave patterns in a spatially extended neural field model.

Parkinson's disease, cortical dysfunction, and alpha-synuclein

The ability to understand how Parkinson's disease neurodegeneration leads to cortical dysfunction will be critical for developing therapeutic advances in Parkinson's disease dementia. The overall purpose of this project was to study the small-amplitude cortical myoclonus in Parkinson's disease as an in vivo model of focal cortical dysfunction secondary to Parkinson's disease neurodegeneration. The objectives were to test the hypothesis that cortical myoclonus in Parkinson's disease is linked to abnormal levels of α-synuclein in the primary motor cortex and to define its relationship to various biochemical, clinical, and pathological measures. The primary motor cortex was evaluated for 11 Parkinson's disease subjects with and 8 without electrophysiologically confirmed cortical myoclonus (the Parkinson's disease + myoclonus group and the Parkinson's disease group, respectively) who had premortem movement and cognitive testing. Similarly assessed 9 controls were used for comparison. Measurements for α-synuclein, Aβ-42 peptide, and other biochemical measures were made in the primary motor cortex. A 36% increase in α-synuclein was found in the motor cortex of Parkinson's disease + myoclonus cases when compared with Parkinson's disease without myoclonus. This occurred without significant differences in insoluble α-synuclein, phosphorylated to total α-synuclein ratio, or Aβ-42 peptide levels. Higher total motor cortex α-synuclein levels significantly correlated with the presence of cortical myoclonus but did not correlate with multiple clinical or pathological findings. These results suggest an association between elevated α-synuclein and the dysfunctional physiology arising from the motor cortex in Parkinson's disease + myoclonus cases. Alzheimer's disease pathology was not associated with cortical myoclonus in Parkinson's disease. Cortical myoclonus arising from the motor cortex is a model to study cortical dysfunction in Parkinson's disease.

Membrane potential-dependent modulation of recurrent inhibition in rat neocortex

Dynamic balance of excitation and inhibition is crucial for network stability and cortical processing, but it is unclear how this balance is achieved at different membrane potentials (V(m)) of cortical neurons, as found during persistent activity or slow V(m) oscillation. Here we report that a V(m)-dependent modulation of recurrent inhibition between pyramidal cells (PCs) contributes to the excitation-inhibition balance. Whole-cell recording from paired layer-5 PCs in rat somatosensory cortical slices revealed that both the slow and the fast disynaptic IPSPs, presumably mediated by low-threshold spiking and fast spiking interneurons, respectively, were modulated by changes in presynaptic V(m). Somatic depolarization (>5 mV) of the presynaptic PC substantially increased the amplitude and shortened the onset latency of the slow disynaptic IPSPs in neighboring PCs, leading to a narrowed time window for EPSP integration. A similar increase in the amplitude of the fast disynaptic IPSPs in response to presynaptic depolarization was also observed. Further paired recording from PCs and interneurons revealed that PC depolarization increases EPSP amplitude and thus elevates interneuronal firing and inhibition of neighboring PCs, a reflection of the analog mode of excitatory synaptic transmission between PCs and interneurons. Together, these results revealed an immediate V(m)-dependent modulation of cortical inhibition, a key strategy through which the cortex dynamically maintains the balance of excitation and inhibition at different states of cortical activity.