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The auditory steady state response (ASSR) arises when periodic sounds evoke stable responses in auditory networks that reflect the acoustic characteristics of the stimuli, such as the amplitude of the sound envelope. Larger for some stimulus rates than others, the ASSR in the human electroencephalogram (EEG) is notably maximal for sounds modulated in amplitude at 40 Hz. To investigate the local circuit underpinnings of the large ASSR to 40 Hz amplitude-modulated (AM) sounds, we acquired skull EEG and local field potential (LFP) recordings from primary auditory cortex (A1) in the rat during the presentation of 20, 30, 40, 50, and 80 Hz AM tones. 40 Hz AM tones elicited the largest ASSR from the EEG acquired above auditory cortex and the LFP acquired from each cortical layer in A1. The large ASSR in the EEG to 40 Hz AM tones was not due to larger instantaneous amplitude of the signals or to greater phase alignment of the LFP across the cortical layers. Instead, it resulted from decreased latency variability (or enhanced temporal consistency) of the 40 Hz response. Statistical models indicate the EEG signal was best predicted by LFPs in either the most superficial or deep cortical layers, suggesting deep layer coordinators of the ASSR. Overall, our results indicate that the recruitment of non-uniform but more temporally consistent responses across A1 layers underlie the larger ASSR to amplitude-modulated tones at 40 Hz.

Stroke is one of the leading causes of disability worldwide. There are many different rehabilitation approaches aimed at improving clinical outcomes for stroke survivors. One of the latest therapeutic techniques is the non-invasive brain stimulation. Among non-invasive brain stimulation, transcranial direct current stimulation has shown promising results in enhancing motor and cognitive recovery both in animal models of stroke and stroke survivors. In this framework, one of the most innovative methods is the bihemispheric transcranial direct current stimulation that simultaneously increases excitability in one hemisphere and decreases excitability in the contralateral one. As bihemispheric transcranial direct current stimulation can create a more balanced modulation of brain activity, this approach may be particularly useful in counteracting imbalanced brain activity, such as in stroke. Given these premises, the aim of the current study has been to explore the recovery after stroke in mice that underwent a bihemispheric transcranial direct current stimulation treatment, by recording their electric brain activity with local field potential and by measuring behavioural outcomes of Grip Strength test. An innovative parameter that explores the complexity of signals, namely the Entropy, recently adopted to describe brain activity in physiopathological states, was evaluated to analyse local field potential data. Results showed that stroke mice had higher values of Entropy compared to healthy mice, indicating an increase in brain complexity and signal disorder due to the stroke. Additionally, the bihemispheric transcranial direct current stimulation reduced Entropy in both healthy and stroke mice compared to sham stimulated mice, with a greater effect in stroke mice. Moreover, correlation analysis showed a negative correlation between Entropy and Grip Strength values, indicating that higher Entropy values resulted in lower Grip Strength engagement. Concluding, the current

Over 2,000 yearly new cases of spinal cord injury (SCI) in Canada leave many people with reduced motor function that leads to secondary health complications. Increasing one’s ability to walk can significantly curtail these complications but there is currently no treatment for recovering locomotor function after SCI in humans. Preclinical research with rodent models was used for my studies described in this dissertation to seek a better understanding of mechanisms underlying the recovery of walking. The purpose of the first study was to examine changes in networks transmitting sensory input to motoneurons between the first and the fifth week after a complete SCI. The hypothesis that afferent input from the tibial nerve (TIB) in the lumbar segments is distributed differently after SCI was examined. A complete spinal transection injury in rats and in vivo electrophysiological measurements of evoked potentials following TIB stimulation were used. TIB afferents evoked intraspinal field potentials in the dorsal horn that showed a significant reduction in amplitude at one-week post-SCI. By five weeks post-SCI, however, TIB afferent transmission efficacy in these pathways was similar in rats without SCI. These findings suggest that TIB afferent input combined with dorsal horn neural excitability of spinal interneurons drives the reorganization needed for recovery of some walking capacity. My second study utilized a genetically modified rat model in which neurons producing serotonin (5-HT) could be activated to escalate locomotor recovery. By using grafting of embryonic 5-HT neurons below the level of SCI, we tested the hypothesis that activation of grafted 5-HT neurons by chemogenetic means in paraplegic rats improves locomotor activity (compared to rats in which only grafting was done). Behavioral analysis by kinematic and hindlimb EMG assessments during treadmill walking were performed before and after chemogenetic stimulation of grafted 5-HT cells and immunohistochemistr

L-DOPA-induced dyskinesia (LID) in Parkinson’s disease has been linked to oscillatory neuronal activities in the cortico-basal ganglia network. We set out to examine the pattern of cortico-basal ganglia oscillations induced by selective agonists of D1 and D2 receptors in a rat model of LID. Local field potentials were recorded in freely moving rats using large-scale electrodes targeting three motor cortical regions, dorsomedial and dorsolateral striatum, external globus pallidus, and substantial nigra pars reticulata. Abnormal involuntary movements were elicited by the D1 agonist SKF82958 or the D2 agonist sumanirole, while overall motor activity was quantified using video analysis (DeepLabCut). Both SKF82958 and sumanirole induced dyskinesia, although with significant differences in temporal course, overall severity, and body distribution. The D1 agonist induced prominent narrowband oscillations in the high gamma range (70–110 Hz) in all recorded structures except for the nigra reticulata. Additionally, the D1 agonist induced strong functional connectivity between the recorded structures and the phase analysis revealed that the primary motor cortex (forelimb area) was leading a supplementary motor area and striatum. Following treatment with the D2 agonist, narrowband gamma oscillations were detected only in forelimb motor cortex and dorsolateral striatum, while prominent oscillations in the theta band occurred in the globus pallidus and nigra reticulata. Our results reveal that the dyskinetic effects of D1 and D2 receptor agonists are associated with distinct patterns of cortico-basal ganglia oscillations, suggesting a recruitment of partially distinct networks.

Distinct lines of research in both humans and animals point to a specific role of the hippocampus in both spatial and episodic memory function. The discovery of concept cells in the hippocampus and surrounding medial temporal lobe (MTL) regions suggests that the MTL maps physical and semantic spaces with a similar neural architecture. Here, we studied the emergence of such maps using MTL microwire recordings from 20 patients (9 female, 11 male) navigating a virtual environment featuring salient landmarks with established semantic meaning. We present several key findings. The array of local field potentials in the MTL contains sufficient information for above-chance decoding of subjects' instantaneous location in the environment. Closer examination revealed that as subjects gain experience with the environment the field potentials come to represent both the subjects' locations in virtual space and in high-dimensional semantic space. Similarly, we observe a learning effect on temporal sequence coding. Over time, field potentials come to represent future locations, even after controlling for spatial proximity. This predictive coding of future states, more so than the strength of spatial representations per se, is linked to variability in subjects' navigation performance. Our results thus support the conceptualization of the MTL as a memory space, representing both spatial- and nonspatial information to plan future actions and predict their outcomes.

Interactive neurorobotics is a subfield which characterizes brain responses evoked during interaction with a robot, and their relationship with the behavioral responses. Gathering rich neural and behavioral data from humans or animals responding to agents can act as a scaffold for the design process of future social robots. This research seeks to study how organisms respond to artificial agents in contrast to biological or inanimate ones. This experiment uses the novel affordances of the robotic platforms to investigate complex dynamics during minimally structured interactions that would be difficult to capture with classical experimental setups. We then propose a general framework for such experiments that emphasizes naturalistic interactions combined with multimodal observations and complementary analysis pipelines that are necessary to render a holistic picture of the data for the purpose of informing robotic design principles. Finally, we demonstrate this approach with an exemplar rat-robot social interaction task which included simultaneous multi-agent tracking and neural recordings.

Objective: This dissertation aims to learn about the neural networks involved with using deep brain stimulation (DBS) to treat Parkinson’s disease (PD) and increase our understanding of the mechanism of DBS. The particular focus is on examining network dynamics in the cortico-basal ganglia (BG) circuit and how DBS modulates functional connectivity in the cortico-BG circuit. The overarching hypothesis of this work is that DBS changes electrophysiological environments to alter the brain’s activity on a network level, examined here in the cortico-BG network in PD. Background: Deep brain stimulation (DBS) is the therapeutic use of chronic electrical stimulation of the brain via an implanted electrode and is a treatment for a variety of neurological disorders. The brain is an electrically active organ, containing neurons that communicate in circuits using action potentials (APs) and local field potentials (LFPs). We can infer information about how neurons communicate by studying these signals, how they behave in PD, and how they respond to DBS. PD is a neurodegenerative disease that manifests motor symptoms of bradykinesia, tremor, and rigidity, as well as a host of non-motor symptoms including cognitive impairment. It is characterized by a loss of dopamine (DA) neurons in the substantia nigra (SN), which has downstream effects on the function of the cortico-BG network. The cortico-BG network is an intricate web of connections between anatomical areas that regulates movement. DBS is used to treat the motor symptoms of PD with widespread success and has long-lasting efficacy. The DBS electrodes are placed into subcortical structures in the cortico-BG network, most commonly the subthalamic nucleus (STN) and the globus pallidus internus (GPi). There are many theories concerning how DBS works, and this project sought to provide increased mechanistic understanding. Empirical evidence attests to the effectiveness of DBS as a treatment for PD and how it must change some patholo

BackgroundClosed-loop phase-locked stimulation experiments are rare due to the unavailability of user-friendly algorithms and devices. Our goal is to provide an algorithm for the detection of oscillatory activity in local field potentials (LFPs) and phase prediction, which is user-friendly and robust to non-stationarities in LFPs of behaving animals.New methodWe propose an algorithm that only requires specification of the frequency range within which oscillatory episodes are tracked. Frequency-specific detection thresholds and filter parameters are adjusted automatically based on the short-time LFP power spectrum. Estimates of instantaneous frequency and instantaneous phase are used for phase extrapolation, taking advantage of Bayesian estimation. We used real LFP signals, recorded from a variety of different species and different brain areas, as well as artificial LFP signals with known properties to assess the detection and prediction performance of our algorithm and three previously published reference algorithms under various conditions.Results and comparison with existing methodsOur algorithm, while significantly more user-friendly than previous approaches, provides a solid detection and prediction performance over a wide range of realistic conditions and, in many cases, has a longer prediction horizon than the reference algorithms. Due to its ability to adjust to changes in the signal, the algorithm is well-prepared to deal with non-stationarities in oscillation frequency, even in the presence of multiple oscillation components.ConclusionsWe have created a universal algorithm for oscillation detection and phase prediction, which performs well and is user-friendly at the same time, making closed-loop phase-locked stimulation experiments easier to accomplish.

Functional magnetic resonance imaging (fMRI) of the spinal cord relies on the integrity of neurovascular coupling (NVC) to infer neuronal activity from hemodynamic changes. Astrocytes are a key component of cerebral NVC, but their role in spinal NVC is unclear. The objective of this study was to examine whether inhibition of astrocyte metabolism by fluorocitrate alters spinal NVC. In 14 rats, local field potential (LFP) and spinal cord blood flow (SCBF) were recorded simultaneously in the lumbosacral enlargement during noxious stimulation of the sciatic nerve before and after a local administration of fluorocitrate (N = 7) or saline (N = 7). Fluorocitrate significantly reduced SCBF responses (p < 0.001) but not LFP amplitude (p = 0.22) compared with saline. Accordingly, NVC was altered by fluorocitrate compared with saline (p < 0.01). These results support the role of astrocytes in spinal NVC and have implications for spinal cord imaging with fMRI for conditions in which astrocyte metabolism may be altered. © 2021, The Author(s).

5-Hydroxytryptamine 2A (5-HT2A) receptor activation may contribute to the psychotomimetic and/or antidepressant effects of psychedelic drugs. 5-HT2A agonists induce broadband changes in neural population activity, including high frequency oscillations (HFO) spanning diverse brain regions, however, the mechanisms and relevance of these oscillations remain unclear. I therefore quantified the effects of a selective 5-HT2A agonist 25I-NBOH (25I) on the behaviour and neurophysiology of freely-behaving adult rats. Local field potentials (LFP) were recorded from rats with electrodes arrays implanted in either cortico-limbic (prefrontal cortex, hippocampus, amygdala; n=5) or cortico-striatal (prefrontal cortex, hippocampus, nucleus accumbens; n=4) circuits. I developed an analysis pipeline encompassing video tracking of behaviour, spectral analysis, functional connectivity, and dynamic causal modelling (DCM). 25I induced visible behavioural changes, though quantification was limited by video resolution and sample size. Spectral analysis confirmed the emergence of HFO throughout cortico-limbic and cortico-striatal circuits, except in hippocampus. Functional connectivity analysis identified increased coupling between the amygdala and prefrontal cortex and implicated the nucleus accumbens as a likely source of HFO. Unexpectedly, changes in undirected (Fourier coherence) and directed (Granger causality) measures of functional connectivity were dissociable, highlighting different facets of these analyses and their interpretation. DCM was used to model 25I’s effects on the cortico-limbic circuit and identified (1) increases in top-down control of amygdala by prefrontal cortex, which may contribute to the antidepressant and anxiolytic effects of psychedelic drugs, and (2) disrupted top-down cortico-hippocampal connections, which may reflect psychotomimetic effects of 5HT2A -agonists. DCM also indicated that t

Oscillatory neural activity in the cortico-basal ganglia-thalamocortical (CBGTC) loop is associated with the motor state of a subject, but also with the availability of modulatory neurotransmitters. For example, increased low-frequency oscillations in Parkinson's disease (PD) are related to decreased levels of dopamine and have been proposed as biomarkers to adapt and optimize therapeutic interventions, such as deep brain stimulation. Using neural oscillations as biomarkers require differentiating between changes in oscillatory patterns associated with parkinsonism vs. those related to a subject's motor state. To address this point, we studied the correlation between neural oscillatory activity in the motor cortex and striatum and varying degrees of motor activity under normal and parkinsonian conditions. Using rats with bilateral or unilateral 6-hydroxydopamine lesions as PD models, we correlated the motion index (MI)-a measure based on the physical acceleration of the head of rats-to the local field potential (LFP) oscillatory power in the 1-80 Hz range. In motor cortices and striata, we observed a robust correlation between the motion index and the oscillatory power in two main broad frequency ranges: a low-frequency range [5.0-26.5 Hz] was negatively correlated to motor activity, whereas a high-frequency range [35.0-79.9 Hz] was positively correlated. We observed these correlations in both normal and parkinsonian conditions. In addition to these general changes in broad-band power, we observed a more restricted narrow-band oscillation [25-40 Hz] in dopamine-denervated hemispheres. This oscillation, which seems to be selective to the parkinsonian state, showed a linear frequency dependence on the concurrent motor activity level. We conclude that, independently of the parkinsonian condition, changes in broad-band oscillatory activities of cortico-basal ganglia networks (including changes in the relative power of low- and high-frequency bands) are closely correlate

A growing interest for Cannabidiol (CBD), a component of Cannabis Sativa, has occurred over the past years. The medical potential of the component is yet to be better characterized, as its effects on sleep, and in particular memory, are to date not well understood or consistently characterized. This master thesis project focuses on analysing the effect of CBD on an anaesthesia-induced sleep-like state in rats, and its effects on the hippocampal sharp-wave-ripples, which have been shown to be associated with memory replay during sleep, and hence system consolidation. The hippocampus and prefrontal cortex, the two structures involved in memory consolidation, were recorded in 19 rats, split in two groups (CBD and vehicle). From these recordings, an automated sleep scorer using principal component analysis was developed to obtain the animals’ hypnograms, which were analysed to study sleep-like structure. From the recordings of the hippocampal pyramidal layer, and an additionnal layer deeper under it, respectively ripples and sharp waves were detected in all animals, and characterized for each group. We observed and demonstrated that CBD changes the sleep-like structure by shortening both REM and NREM bouts, resulting in an increase in transitions between both states. Additionally, we observed that, although ripples are not significantly different between both groups, sharp waves tend to be smaller among CBD animals. Lastly we noticed that both sharp wave and ripple activity, after increasing upon transition to NREM, decreases as the bout last. This finding suggests that vehicle animals, who have longer bouts and less transitions, would display less sharp wave and ripple activity, although we found no significant difference in the amount of both brain events. This paradox suggests that there is still more to characterize in order to understand if CBD enhances or not memory consolidation. In sum, CBD changes anaesthesia-induced sleep by shortening the duration of both NRE

The functional consequences of ischemic stroke in the remote brain regions are not well characterized. The current study sought to determine changes in hippocampal oscillatory activity that may underlie the cognitive impairment observed following distal middle cerebral artery occlusion (dMCAO) without causing hippocampal structural damage. Local field potentials were recorded from the dorsal hippocampus and cortex in urethane-anesthetized rats with multichannel silicon probes during dMCAO and reperfusion, or mild ischemia induced by bilateral common carotid artery occlusion (CCAO). Bilateral change of brain state was evidenced by reduced theta/delta amplitude ratio and shortened high theta duration following acute dMCAO but not CCAO. An aberrant increase in the occurrence of sharp-wave-associated ripples (150-250 Hz), crucial for memory consolidation, was only detected after dMCAO reperfusion, coinciding with an increased occurrence of high-frequency discharges (250-450 Hz). dMCAO also significantly affected the modulation of gamma amplitude in the cortex coupled to hippocampal theta phase, although both hippocampal theta and gamma power were temporarily decreased during dMCAO. Our results suggest that MCAO may disrupt the balance between excitatory and inhibitory circuits in the hippocampus and alter the function of cortico-hippocampal network, providing a novel insight in how cortical stroke affects function in remote brain regions.

BackgroundThe synchronous ionic currents that give rise to neural oscillations have complex influences on neuronal spiking activity that are challenging to characterize.New methodHere we present a method to estimate probabilistic relationships between neural spiking activity and the phase of field oscillations using a generalized linear model (GLM) with an overcomplete basis of circular functions. We first use an L1-regularized maximum likelihood procedure to select an active set of regressors from the overcomplete set and perform model fitting using standard maximum likelihood estimation. An information theoretic model selection procedure is then used to identify an optimal subset of regressors and associated coefficients that minimize overfitting. To assess goodness of fit, we apply the time-rescaling theorem and compare model predictions to original data using quantile-quantile plots.ResultsSpike-phase relationships in synthetic data were robustly characterized. When applied to in vivo hippocampal data from an awake behaving rat, our method captured a multimodal relationship between the spiking activity of a CA1 interneuron, a theta (5-10 Hz) rhythm, and a nested high gamma (65-135 Hz) rhythm.Comparison with existing methodsPrevious methods for characterizing spike-phase relationships are often only suitable for unimodal relationships, impose specific relationship shapes, or have limited ability to assess the accuracy or fit of their characterizations.ConclusionsThis method advances the way spike-phase relationships are visualized and quantified, and captures multimodal spike-phase relationships, including relationships with multiple nested rhythms. Overall, our method is a powerful tool for revealing a wide range of neural circuit interactions.

Neurological examination remains the primary clinical investigation in patients with spinal cord injury. However, neuroimaging methods such as functional magnetic resonance imaging (fMRI) are promising tools for following functional changes in the course of injury, disease and rehabilitation. However, the relationship between neuronal activity and blood flow in the spinal cord on which fMRI relies has been largely overlooked. The objective of this study was to examine neurovascular coupling in the spinal cord of decerebrated rats during electrical stimulation of the sciatic nerve with and without isoflurane anesthesia (1.2%). Local field potentials (LFP) and spinal cord blood flow (SCBF) were recorded simultaneously in the lumbosacral enlargement. Isoflurane did not significantly alter LFP (p = 0.53) and SCBF (p = 0.57) amplitude. Accordingly, neurovascular coupling remained comparable with or without isoflurane anesthesia (p = 0.39). These results support the use of isoflurane in rodents to investigate nociceptive functions of the spinal cord using fMRI. © 2018, The Physiological Society of Japan and Springer Japan KK, part of Springer Nature.

The piriform cortex is critically involved in our sense of smell and engages with the olfactory network via specific neural oscillations. It is also considered to be common node of the focal epilepsy network however it is unknown if it plays a role in absence epilepsy. The main focus of this thesis was to determine whether there is any pre-seizure involvement of the piriform cortex in absence epilepsy. Using a rat model of absence epilepsy and non-epileptic controls, multi-channel microelectrode arrays were implanted in the piriform cortex and mediodorsal thalamus, the piriform cortex’s direct link to thalamo-cortical networks underlying absence epilepsy, to record multiunit clusters and field potentials. Three distinct signal processing analyses were developed and applied to the study of the pre-seizure onset connectivity changes in the piriform cortex which encompass four distinct but interrelated research aims. The first aim was to determine the transient firing patterns of multiunit clusters within and between the piriform cortex and mediodorsal thalamus around the onset of absence seizures. The phase locking between multiunit cluster spikes and neural oscillations (spike-LFP phase locking) which govern olfactory network communication was shown to change within the piriform cortex prior to seizure onset, suggesting it contributes to seizure initiation. Early changes in spike-LFP phase locking suggested possible pre-seizure onset changes in local and long range functional connectivity of the piriform cortex and mediodorsal thalamus. A critical issue of analysing functional connectivity using microelectrode arrays is overlapping effect of neighbouring electrodes. Hence the second aim of this thesis was determining the optimal method for resolving the effect of neighbouring electrodes to accurately estimate functional connectivity. Band-amplitude fluctuation orthogonalization followed by inter-site phase clustering estimates was shown to be the optimal method. This

[ES] La mayor parte de la información que procesa nuestro cerebro se realiza a través de potenciales eléctricos que viajan mediante los circuitos neuronales. La actividad eléctrica específica de cada neurona se conoce como potencial de acción. Estos se producen debido a la polarización y despolarización de la célula. Cuando la neurona recibe un impulso eléctrico, y esta estimulación supera un cierto umbral, se genera este disparo de actividad. Además, la actividad conjunta de un gran número de neuronas permite sumar sus contribuciones eléctricas, generando un campo eléctrico tan grande que podemos detectarlo fuera del propio cráneo a través de la electroencefalografía. No obstante, al encontrarnos tan lejos de la fuente de corriente, nuestra lectura es un promedio de toda la actividad cerebral, de modo que no podemos saber a qué región concreta pertenece. Es por ello qué se utilizan electrodos intracraneales implantados directamente en aquella zona que sea de interés, pudiendo medir los cambios eléctricos específicos de la población neuronal que rodea al electrodo. El problema reside en reconocer a que célula pertenece cada uno de estos potenciales de acción que se registran. Se aborda este problema a través de la morfología concreta del potencial de acción. Debido a que existe una propagación desde la célula hasta el contacto, la señal eléctrica se deforma en este trayecto. Por ejemplo, si la actividad es muy cercana tendrá amplitudes mayores que si está más alejada. El funcionamiento anormal de un grupo de neuronas puede tener graves consecuencias, incluyendo la provocación de ataques epilépticos. En concreto, esta enfermedad es debida al exceso de actividad eléctrica sincrónica que nace en una región específica, en este caso en el hipocampo, y que se va a extender por todo el cerebro. El objetivo de este Trabajo Fin de Grado es el estudio de la propagación de esta actividad eléctrica analizando los potenciales de acción de las neuronas. Una vez identificada y cla, [EN] Most of the information that our brain processes is done through electrical potentials that travel by way of neural circuits. The specific electrical activity of each neuron is known as action potential. These are produced due to the polarization and depolarization of the cell. When the neuron receives an electric impulse, and this stimulation exceeds a certain threshold, this activity trigger is generated. Furthermore, the joint activity of a large number of neurons allows to add their electrical contributions, generating an electric field so large that we can detect it outside the skull itself through the electroencephalography. However, by finding ourselves so far away from the current source, our reading is an average of all brain activity, so we can't know which specific region it belongs to. That is why intracranial electrodes are used directly in the area that is of interest, being able to measure the specific electrical changes to the neuronal population surrounding the electrode. The problem lies in recognizing that cell belongs to each of these action potentials that are recorded. This problem is addressed through the specific morphology of the action potential. Because there is a spread from the cell to the contact, the electrical signal is deformed in this way. For example, if the activity is very close it will have greater amplitudes than if it is farther away. The abnormal functioning of a group of neurons may have serious consequences, including the provocation of epileptic seizures. In particular, this disease is due to the excess of synchronous electrical activity that is born in a specific region, in this case in the hippocampus, and that it will spread all over the brain. The objective of this end-of-degree work is to study the propagation of this electrical activity by analyzing the action potentials of neurons. Once all neuronal activity is identified and classified, it is intended to study its behavior in the face of various stimuli, both

Simultaneous recordings from large populations of individual neurons across distributed brain regions over months to years will enable new avenues of scientific and clinical development. The use of flexible polymer electrode arrays can support long-lasting recording, but the same mechanical properties that allow for longevity of recording make multiple insertions and integration into a chronic implant a challenge. Here is a methodology by which multiple polymer electrode arrays can be targeted to a relatively spatially unconstrained set of brain areas. The method utilizes thin-film polymer devices, selected for their biocompatibility and capability to achieve long-term and stable electrophysiologic recording interfaces. The resultant implant allows accurate and flexible targeting of anatomically distant regions, physical stability for months, and robustness to electrical noise. The methodology supports up to sixteen serially inserted devices across eight different anatomic targets. As previously demonstrated, the methodology is capable of recording from 1024 channels. Of these, the 512 channels in this demonstration used for single neuron recording yielded 375 single units distributed across six recording sites. Importantly, this method also can record single units for at least 160 days. This implantation strategy, including temporarily bracing each device with a retractable silicon insertion shuttle, involves tethering of devices at their target depths to a skull-adhered plastic base piece that is custom-designed for each set of recording targets, and stabilization/protection of the devices within a silicone-filled, custom-designed plastic case. Also covered is the preparation of devices for implantation, and design principles that should guide adaptation to different combinations of brain areas or array designs.

Neurological examination remains the primary clinical investigation in patients with spinal cord injury. However, neuroimaging methods such as functional magnetic resonance imaging (fMRI) are promising tools for following functional changes in the course of injury, disease and rehabilitation. However, the relationship between neuronal activity and blood flow in the spinal cord on which fMRI relies has been largely overlooked. The objective of this study was to examine neurovascular coupling in the spinal cord of decerebrated rats during electrical stimulation of the sciatic nerve with and without isoflurane anesthesia (1.2%). Local field potentials (LFP) and spinal cord blood flow (SCBF) were recorded simultaneously in the lumbosacral enlargement. Isoflurane did not significantly alter LFP (p = 0.53) and SCBF (p = 0.57) amplitude. Accordingly, neurovascular coupling remained comparable with or without isoflurane anesthesia (p = 0.39). These results support the use of isoflurane in rodents to investigate nociceptive functions of the spinal cord using fMRI. © 2018, The Physiological Society of Japan and Springer Japan KK, part of Springer Nature.

In Parkinson's disease (PD), subthalamic nucleus beta band oscillations are decreased by therapeutic deep-brain stimulation (DBS) and this has been proposed as important to the mechanism of therapy. The globus pallidus is a common alternative target for PD with similar motor benefits as subthalamic DBS, but effects of pallidal stimulation in PD are not well studied, and effects of pallidal DBS on cortical function in PD are unknown. Here, in 20 PD and 14 isolated dystonia human patients of both genders undergoing pallidal DBS lead implantation, we recorded local field potentials from the globus pallidus and in a subset of these, recorded simultaneous sensorimotor cortex ECoG potentials. PD patients had elevated resting pallidal low beta band (13-20 Hz) power compared with dystonia patients, whereas dystonia patients had elevated resting pallidal theta band (4-8 Hz) power compared with PD. We show that this results in disease-specific patterns of interaction between the pallidum and motor cortex: PD patients demonstrated relatively elevated phase coherence with the motor cortex in the beta band and this was reduced by therapeutic pallidal DBS. Dystonia patients had greater theta band phase coherence. Our results support the hypothesis that specific motor phenomenology observed in movement disorders are associated with elevated network oscillations in specific frequency bands, and that DBS in movement disorders acts in general by disrupting elevated synchronization between basal ganglia output and motor cortex.SIGNIFICANCE STATEMENT Perturbations in synchronized oscillatory activity in brain networks are increasingly recognized as important features in movement disorders. The globus pallidus is a commonly used target for deep-brain stimulation (DBS) in Parkinson's disease (PD), however, the effects of pallidal DBS on basal ganglia and cortical oscillations are unknown. Using invasive intraoperative recordings in patients with PD and isolated dystonia, we found disease

Implantable neural prostheses are in widespread use for treating a variety of brain disorders. Until recently, most implantable brain devices have been unidirectional, either delivering neurostimulation without brain sensing, or sensing brain activity to drive external effectors without a stimulation component. Further, many neural interfaces that incorporate a sensing function have relied on hardwired connections, such that subjects are tethered to external computers and cannot move freely. A new generation of neural prostheses has become available, that are both bidirectional (stimulate as well as record brain activity) and totally implantable (no externalized connections). These devices provide an opportunity for discovering the circuit basis for neuropsychiatric disorders, and to prototype personalized neuromodulation therapies that selectively interrupt neural activity underlying specific signs and symptoms.

While signatures of attention can be observed in widespread areas within and outside of cortex, the control of attention is thought to be regulated by higher cognitive brain areas, such as the prefrontal cortex. In their recent study on mice Kim et al. could show that successful allocation of attention is characterized by increased spiking of a specific type of inhibitory interneurons, the parvalbumin neurons, and higher oscillatory activity in the gamma band in the local prefrontal network. It was recently demonstrated that encoding of working memory in prefrontal areas is linked to bursts of gamma oscillations, a discontinuous network process characterized by short periods of intense power in the gamma band. The relationship between attention and working memory is unclear, and it is possible that these two cognitive processes share encoding principles. To address this gap, the electrophysiological data collected in the Carlén Lab have been analyzed with advanced spatio-temporal approaches. In particular, we have analyzed bursting gamma activity in medial prefrontal cortex during attentional processing and investigated the similarities to gamma bursting observed during working memory. Gamma-band bursts during attention were reliably detected with several methods. We have characterized several features of the bursts, including the occurrence, duration and amplitude. The neuronal firing rates during and outside of bursts have also been computed. We investigated the correlation between different criteria characterizing the gamma burst and successful vs failed allocation of attention. Control data were generated to discuss the obtained results. The aim of the study was to explore the hypothesis that the medial prefrontal cortex encodes attention trough gamma bursts, which could reveal some similarities and differences in coding of central cognitive processes. No clear difference was found in the characterization between successful and failed allocation of attention. In, Även fast flera olika hjärnområdens aktivitet kan korreleras med uppmärksamhet, anses kontrollen av uppmärksamhet regleras av högre kognitiva hjärnområden, såsom främre hjärnbarken. I en nyligen publicerad artikel studerade Kim et al. hjärnaktiviteten hos möss och kunde visa att en framgångsrik uppmärksamhet kännetecknas av en ökad aktivitet av en specifik typ av inhiberande nervceller, parvalbumin celler, och högre oscillerande aktivitet i gammafrekvens i främre hjärnbarkens lokala nätverk. Det har nyligen visats att kodning av arbetsminne i främre hjärnbarken är kopplat till utbrott av gamma-oscillationer, en diskontinuerlig nätverksprocess som kännetecknas av korta perioder av intensiva oscillationer av det lokala nätverket i gammafrekvens . Relationen mellan uppmärksamhet och arbetsminne är oklar, och det är möjligt att dessa två kognitiva processer delar kodningsprinciper. För att minska detta gap av kunskap har den elektrofysiologiska datan som samlats in i Carlén Lab analyserats med avancerade spatio-temporala tillvägagångssätt. I synnerhet har vi analyserat utbrott i gammaaktivitet i främre hjärnbarken under uppmärksamhet och undersökt likheterna med gamma- utbrott observerade under arbetsminne. Gamma-bandutbrott under uppmärksamhet påvisades på ett tillförlitligt sätt med flera metoder. Vi har karaktäriserat flera funktioner hos utbrotten, inklusive förekomsten, varaktigheten och amplituden. De enskilda cellernas aktivitet undersöktes även under och utanför utprotten av gamma-oscillationer. Vi undersökte sambandet mellan de olika kriterier som karakteriserar gamma-utbrott under framgångsrik mot misslyckad allokering av uppmärksamhet. Kontrolldata genererades för att diskutera de erhållna resultaten. Syftet med studien var att utforska hypotesen att den främre hjärnbarken kodar uppmärksamhet genom gamma-utbrott, vilket kan avslöja vissa likheter och skillnader i kodning av centrala kognitiva processer. Ingen klar skillnad hittades i karaktäriseringen mellan

Signal Analysis techniques are routinely used in Neuroscience to interpret raw signals harvested from the Nervous System. From a simple Fourier analysis to more complicated methods such as multiresolution wavelet analysis, such techniques must be used for signal manipulation in order to reach informed conclusions on the measurements taking place. In neuroscientific research, it is common practice to scan a neural recording manually to label the areas of the signal that are relevant to the research at hand. This can, obviously, be very time-consuming for the researchers. What is more, this method can prove imperfect, seeing as two different researchers can disagree on the labeling of the data. In every experiment, signal epochs are isolated because they stand out from the rest of the recording due to a special characteristic, which is, in the previous case, visible with the unaided eye. In signal processing terms, this means that the signal displays specific spectrotemporal characteristics during these epochs. Thus, these characteristics can be isolated, quantified and studied independently, while a detection algorithm can be developed so that the detection and labeling of the significant signal epochs can be carried out automatically. In this project, the spontaneous activity of the neurons in the Prefrontal Cortex was analyzed in relation to neural synchrony, using time-varying ARModels. It was concluded that the signal epochs of neural synchrony display common characteristics besides being visually similar. This allowed the isolation of the synchrony epochs based on model parameters. However, the training of the models is very computationally intensive, so a detection algorithm was developed, based on a matched filter which made use of one of the isolated epochs as a template. The detection scheme was then validated using a recording harvested during electrical stimulation of the deep brain, evaluating the quality of the scheme, Biomedical Engineering

[Background] Deep Brain Stimulation (DBS) of the subgenual cingulate cortex (SCC) is a promising therapeutic alternative to treat resistant major depressive disorder. In preclinical studies, DBS of the ventromedial prefrontal cortex (vmPFC, the rodent SCC correlate) provokes an antidepressant-like effect, along with changes in noradrenaline levels at the site of stimulation. Hence, DBS appears to activate the noradrenergic-locus coeruleus (LC) system., [Objective/Hypothesis] The aim of this study was to evaluate the effect of vmPFC DBS on the electrical activity of noradrenergic LC neurons, cortical oscillations and coherence between both brain areas in male rats., [Methods] The antidepressant-like effect of vmPFC DBS was evaluated through the forced swimming test. Tonic and evoked activity of LC neurons, LC activity of alpha2-adrenoceptors, local field potentials from LC and electrocorticogram signals were studied after DBS by electrophysiological recordings in anaesthetized rats. The effect of DBS on tyrosine hydroxylase (TH), noradrenaline transporters (NAT), phosphorylation of the extracellular signal–regulated kinase (ERK) and corticotropin releasing factor (CRF) expression in the LC were measured by western blot assays., [Results] DBS induced an antidepressant-like effect increasing climbing behaviour in the FST that was accompanied by a robust increase of TH expression in the rat LC. The tonic and evoked activity of LC neurons was enhanced by DBS, which impaired alpha2-adrenoceptors activity. DBS also promoted an increase in slow LC oscillations, as well as a shift in LC-cortical coherence., [Conclusion] DBS of the vmPFC appears to affect the LC, producing changes that may underlie its antidepressant-like effects.

OBJECTIVE: Adaptive deep brain stimulation (aDBS) controlled by local field potentials (LFPs) is considered a promising treatment for advanced Parkinson's disease (PD). The clinical research investigating aDBS functioning is performed using external deep brain stimulation (DBS) systems that require LFP recording through the temporary externalization of DBS leads. Although research examining LFP was first undertaken more than 20 years ago, only a few studies concern lead externalization and LFP recording safety. In the present retrospective study, we assessed the risk of infection related to these procedures. METHODS: A total of 105 patients with PD who underwent DBS surgery and lead externalization at our hospital from 2002 to 2014 were included in the present study. The medical records were used to collect clinical data and information concerning surgical site infections. We assessed the infection incidence in our cohort and the risk of infection related to the LFP recording procedure. RESULTS: The incidence of infections in patients who underwent lead externalization was 2.8%, which was consistent with the postoperative infectious risk reported in the literature (Wilcoxon signed rank test; P > 0.05). Moreover, the LFP recording procedure did not significantly increase the infection risk (LFP recordings vs. no LFP recordings: 2.5% vs. 4.2%; Fisher exact test; P > 0.05). CONCLUSIONS: DBS lead externalization and LFP recording are safe and do not increase the postoperative infection risk in patients with PD who undergo DBS surgery. Our retrospective study supported further clinical research in the field of LFP-based aDBS.

Laminar population analysis (LPA) is a method for analysis of electrical data recorded by linear multielectrodes passing through all lamina of cortex. Like principal components analysis (PCA) and independent components analysis (ICA), LPA offers a way to decompose the data into contributions from separate cortical populations. However, instead of using purely mathematical assumptions in the decomposition, LPA is based on physiological constraints, i.e., that the observed LFP (low-frequency part of signal) is driven by action-potential firing as observed in the MUA (multi-unit activity; high-frequency part of the signal). In the presently developed generalized laminar population analysis (gLPA) the set of basis functions accounting for the LFP data is extended compared to the original LPA, thus allowing for a better fit of the model to experimental data. This enhances the risk for overfitting, however, and we therefore tested various versions of gLPA on virtual LFP data in which we knew the ground truth. These synthetic data were generated by biophysical forward-modeling of electrical signals from network activity in the comprehensive, and well-known, thalamocortical network model developed by Traub and coworkers. The results for the Traub model imply that while the laminar components extracted by the original LPA method overall are in fair agreement with the ground-truth laminar components, the results may be improved by use of gLPA method with two (gLPA-2) or even three (gLPA-3) postsynaptic LFP kernels per laminar population.

ObjectiveQuantifying the relationship between microelectrode-recorded multi-unit activity (MUA) and local field potentials (LFPs) in distinct brain regions can provide detailed information on the extent of functional connectivity in spatially widespread networks. These methods are common in studies of cognition using non-human animal models, but are rare in humans. Here we applied a neuronal spike-triggered impulse response to electrophysiological recordings from the human epileptic brain for the first time, and we evaluate functional connectivity in relation to brain areas supporting the generation of seizures.ApproachBroadband interictal electrophysiological data were recorded from microwires adapted to clinical depth electrodes that were implanted bilaterally using stereotactic techniques in six presurgical patients with medically refractory epilepsy. MUA and LFPs were isolated in each microwire, and we calculated the impulse response between the MUA on one microwire and the LFPs on a second microwire for all possible MUA/LFP pairs. Results were compared to clinical seizure localization, including sites of seizure onset and interictal epileptiform discharges.Main resultsWe detected significant interictal long-range functional connections in each subject, in some cases across hemispheres. Results were consistent between two independent datasets, and the timing and location of significant impulse responses reflected anatomical connectivity. However, within individual subjects, the spatial distribution of impulse responses was unique. In two subjects with clear seizure localization and successful surgery, the epileptogenic zone was associated with significant impulse responses.SignificanceThe results suggest that the spike-triggered impulse response can provide valuable information about the neuronal networks that contribute to seizures using only interictal data. This technique will enable testing of specific hypotheses regarding functional connectivity in epilepsy

We undertook a detailed analysis of population spike rate and LFP power in the Zebra finch auditory system. Utilizing the full range of Zebra finch vocalizations and dual-hemisphere multielectrode recordings from auditory neurons, we used encoder models to show how intuitive acoustic features such as amplitude, spectral shape and pitch drive the spike rate of individual neurons and LFP power on electrodes. Using ensemble decoding approaches, we show that these acoustic features can be successfully decoded from the population spike rate vector and the power spectra of the multielectrode LFP with comparable performance. In addition we found that adding pairwise spike synchrony to the spike rate decoder boosts performance above that of the population spike rate alone, or LFP power spectra. We also found that decoder performance grows quickly with the addition of more neurons, but there is notable redundancy in the population code. Finally, we demonstrate that LFP power on an electrode can be well predicted by population spike rate and spike synchrony. High frequency LFP power (80-190Hz) integrates neural activity spatially over a distance of up to 250 microns, while low frequency LFP power (0-30Hz) can integrate neural activity originating up to 800 microns away from the recording electrode.To understand how an auditory system processes complex sounds, it is essential to understand how the temporal envelope of sounds, i.e. the time-varying amplitude, is encoded by neural activity. We studied the temporal envelope of Zebra finch vocalizations, and show that it exhibits modulations in the 0-30Hz range, similar to human speech. We then built linear filter models to predict 0-30Hz LFP activity from the temporal envelopes of vocalizations, achieving surprisingly high performance for electrodes near thalamorecipient areas of Zebra finch auditory cortex. We then show that there are two spatially-distinct subnetworks that resonate at different frequency bands, one subnetwork t

ObjectiveBrain-machine interfaces (BMIs) seek to enable people with movement disabilities to directly control prosthetic systems with their neural activity. Current high performance BMIs are driven by action potentials (spikes), but access to this signal often diminishes as sensors degrade over time. Decoding local field potentials (LFPs) as an alternative or complementary BMI control signal may improve performance when there is a paucity of spike signals. To date only a small handful of LFP decoding methods have been tested online; there remains a need to test different LFP decoding approaches and improve LFP-driven performance. There has also not been a reported demonstration of a hybrid BMI that decodes kinematics from both LFP and spikes. Here we first evaluate a BMI driven by the local motor potential (LMP), a low-pass filtered time-domain LFP amplitude feature. We then combine decoding of both LMP and spikes to implement a hybrid BMI.ApproachSpikes and LFP were recorded from two macaques implanted with multielectrode arrays in primary and premotor cortex while they performed a reaching task. We then evaluated closed-loop BMI control using biomimetic decoders driven by LMP, spikes, or both signals together.Main resultsLMP decoding enabled quick and accurate cursor control which surpassed previously reported LFP BMI performance. Hybrid decoding of both spikes and LMP improved performance when spikes signal quality was mediocre to poor.SignificanceThese findings show that LMP is an effective BMI control signal which requires minimal power to extract and can substitute for or augment impoverished spikes signals. Use of this signal may lengthen the useful lifespan of BMIs and is therefore an important step towards clinically viable BMIs.

Electrical extracellular recordings, i.e., recordings of the electrical potentials in the extracellular medium between cells, have been a main work-horse in electrophysiology for almost a century. The high-frequency part of the signal (>500 Hz), i.e., the multi-unit activity (MUA), contains information about the firing of action potentials in surrounding neurons, while the low-frequency part, the local field potential (LFP), contains information about how these neurons integrate synaptic inputs. As the recorded extracellular signals arise from multiple neural processes, their interpretation is typically ambiguous and difficult. Fortunately, a precise biophysical modeling scheme linking activity at the cellular level and the recorded signal has been established: the extracellular potential can be calculated as a weighted sum of all transmembrane currents in all cells located in the vicinity of the electrode. This computational scheme can considerably aid the modeling and analysis of MUA and LFP signals. Here, we describe LFPy, an open source Python package for numerical simulations of extracellular potentials. LFPy consists of a set of easy-to-use classes for defining cells, synapses and recording electrodes as Python objects, implementing this biophysical modeling scheme. It runs on top of the widely used NEURON simulation environment, which allows for flexible usage of both new and existing cell models. Further, calculation of extracellular potentials using the line-source-method is efficiently implemented. We describe the theoretical framework underlying the extracellular potential calculations and illustrate by examples how LFPy can be used both for simulating LFPs, i.e., synaptic contributions from single cells as well a populations of cells, and MUAs, i.e., extracellular signatures of action potentials., QC 20140314

Evidence suggests that the disruption of circadian rhythms has a negative impact on memory retention. It is therefore speculated that circadian disruption influences some property of sleep responsible for memory retention, but little is known about this relationship. In order to investigate this question, we have continuously recorded local field potentials in the hippocampus and prefrontal cortex of freely behaving adult male Long Evans rats. The current analysis indicates that daily quantities of sleep are strongly maintained in an acute circadian shift. Furthermore, hourly sleep distributions are largely maintained during the shift. Contrastingly, an acute circadian shift is able to alter the hourly distribution of vigilance states and sleep based events predominantly across pre-entrainment to post-entrainment, supporting previous findings of memory retention deficits observed during post-entrainment but not shifting epochs. Furthermore, current analysis suggests that pre-entrainment hourly distributions are conserved, but relocated in phase with post-entrainment.

Cortical spreading depression (SD) has been known for more than 70 years. It has been a unique method investigating basic neurophysiology. A growing body of evidence indicates SD is involved in clinical conditions such as migraine with aura, subarachnoid hemorrhage, and traumatic brain injury. In this chapter we describe the application of SD in studying neurovascular and neurometabolic coupling in rat cerebral cortex. Description of the different techniques (electrophysiology, laser-Doppler flowmetry, and oxygen-sensitive electrodes) is followed by in depth step-by-step instructions on how to use them. This chapter will also describe the vascular consequences of SD and how to elicit SD experimentally.

Neural networks in vertebrates exhibit endogenous oscillations that have been associated with functions ranging from sensory processing to locomotion. It remains unclear whether oscillations may play a similar role in the insect brain. We describe a novel "whole brain" readout for Drosophila melanogaster using a simple multichannel recording preparation to study electrical activity across the brain of flies exposed to different sensory stimuli. We recorded local field potential (LFP) activity from >2,000 registered recording sites across the fly brain in >200 wild-type and transgenic animals to uncover specific LFP frequency bands that correlate with: 1) brain region; 2) sensory modality (olfactory, visual, or mechanosensory); and 3) activity in specific neural circuits. We found endogenous and stimulus-specific oscillations throughout the fly brain. Central (higher-order) brain regions exhibited sensory modality-specific increases in power within narrow frequency bands. Conversely, in sensory brain regions such as the optic or antennal lobes, LFP coherence, rather than power, best defined sensory responses across modalities. By transiently activating specific circuits via expression of TrpA1, we found that several circuits in the fly brain modulate LFP power and coherence across brain regions and frequency domains. However, activation of a neuromodulatory octopaminergic circuit specifically increased neuronal coherence in the optic lobes during visual stimulation while decreasing coherence in central brain regions. Our multichannel recording and brain registration approach provides an effective way to track activity simultaneously across the fly brain in vivo, allowing investigation of functional roles for oscillations in processing sensory stimuli and modulating behavior.

The deficiency in the mitochondrial aspartate/glutamate transporter Aralar/AGC1 results in a loss of the malate-aspartate NADH shuttle in the brain neurons, hypomyelination, and additional defects in the brain metabolism. We studied the development of cortico/hippocampal local field potential (LFP) in Aralar/AGC1 knockout (KO) mice. Laminar profiles of LFP, evoked potentials, and unit activity were recorded under anesthesia in young (P15 to P22) Aralar-KO and control mice as well as control adults. While LFP power increased 3 to 7 times in both cortex and hippocampus of control animals during P15 to P22, the Aralar-KO specimens hardly progressed. The divergence was more pronounced in the CA3/hilus region. In parallel, spontaneous multiunit activity declined severely in KO mice. Postnatal growth of hippocampal-evoked potentials was delayed in KO mice, and indicated abnormal synaptic and spike electrogenesis and reduced output at P20 to P22. The lack of LFP development in KO mice was accompanied by the gradual appearance of epileptic activity in the CA3/hilus region that evolved to status epilepticus. Strikingly, CA3 bursts were poorly conducted to the CA1 field. We conclude that disturbed substrate supply to neuronal mitochondria impairs development of cortico-hippocampal LFPs. Aberrant neuronal electrogenesis and reduced neuron output may explain circuit dysfunction and phenotype deficiencies. © 2012 ISCBFM All rights reserved.

Multielectrode array recordings of extracellular electrical field potentials along the depth axis of the cerebral cortex are gaining popularity as an approach for investigating the activity of cortical neuronal circuits. The low-frequency band of extracellular potential, i.e., the local field potential (LFP), is assumed to reflect synaptic activity and can be used to extract the laminar current source density (CSD) profile. However, physiological interpretation of the CSD profile is uncertain because it does not disambiguate synaptic inputs from passive return currents and does not identify population-specific contributions to the signal. These limitations prevent interpretation of the CSD in terms of synaptic functional connectivity in the columnar microcircuit. Here we present a novel anatomically informed model for decomposing the LFP signal into population-specific contributions and for estimating the corresponding activated synaptic projections. This involves a linear forward model, which predicts the population-specific laminar LFP in response to synaptic inputs applied at different positions along each population and a linear inverse model, which reconstructs laminar profiles of synaptic inputs from laminar LFP data based on the forward model. Assuming spatially smooth synaptic inputs within individual populations, the model decomposes the columnar LFP into population-specific contributions and estimates the corresponding laminar profiles of synaptic input as a function of time. It should be noted that constant synaptic currents at all positions along a neuronal population cannot be reconstructed, as this does not result in a change in extracellular potential. However, constraining the solution using a priori knowledge of the spatial distribution of synaptic connectivity provides the further advantage of estimating the strength of active synaptic projections from the columnar LFP profile thus fully specifying synaptic inputs.

The specific microscopic origins of electromagnetic (EM) fields in excitable cell tissue have been underdetermined for a long time. A better understanding of the microscopic EM field origins directly facilitates an understanding of the origins of EEG and MEG signals, along with the role of EM coupling in cell excitability, developmental cues, regulatory processes underlying learning, and the general brain dynamics involved in all of these and of cognition generally. With the aim of isolating and describing the most plausible originating mechanism, the fundamental laws of electromagnetism, as applied to excitable cell tissue, were subjected to an extended review. A bridging form of the macroscopic EM volume conduction equations was constructed that was specially adapted to reveal the microscopic origins of the endogenous EM fields. The basis of the specialization was a focus on coherence between regions of transmembrane current activity expressed by a neuron during the passage of an action potential throughout its structure. A computational exploration of the equations, applied to a large, biologically realistic pyramidal cell, demonstrated that the coherent transmembrane current activity of spiking neurons can express a faint, unified, spatially extended, “line-of-sight-active” extra-neural EM field with complex structure and dynamics, all based on the operation of individual dipoles created by single ion channels, small ion channel aggregates, and large aggregates of the kind found in the synaptic cleft and elsewhere. The result is highly suggestive of an additional “line-of-sight” regulatory mechanism implemented as feedback delivered by EM coupling. This is consistent with recent empirical observations suggesting that this mechanism exists and operates in cortical tissue.

The local field potential (LFP) is among the most important experimental measures when probing neural population activity, but a proper understanding of the link between the underlying neural activity and the LFP signal is still missing. Here we investigate this link by mathematical modeling of contributions to the LFP from a single layer-5 pyramidal neuron and a single layer-4 stellate neuron receiving synaptic input. An intrinsic dendritic low-pass filtering effect of the LFP signal, previously demonstrated for extracellular signatures of action potentials, is seen to strongly affect the LFP power spectra, even for frequencies as low as 10 Hz for the example pyramidal neuron. Further, the LFP signal is found to depend sensitively on both the recording position and the position of the synaptic input: the LFP power spectra recorded close to the active synapse are typically found to be less low-pass filtered than spectra recorded further away. Some recording positions display striking band-pass characteristics of the LFP. The frequency dependence of the properties of the current dipole moment set up by the synaptic input current is found to qualitatively account for several salient features of the observed LFP. Two approximate schemes for calculating the LFP, the dipole approximation and the two-monopole approximation, are tested and found to be potentially useful for translating results from large-scale neural network models into predictions for results from electroencephalographic (EEG) or electrocorticographic (ECoG) recordings., QC 20120221

[Background and purpose]: F15599, a novel 5-hydroxytryptamine (5-HT)1A receptor agonist with 1000-fold selectivity for 5-HT compared with other monoamine receptors, shows antidepressant and procognitive activity at very low doses in animal models. We examined the in vivo activity of F15599 at somatodendritic autoreceptors and postsynaptic 5-HT1A heteroreceptors., [Experimental approach]: In vivo single unit and local field potential recordings and microdialysis in the rat., [Key results]: F15599 increased the discharge rate of pyramidal neurones in medial prefrontal cortex (mPFC) from 0.2 µg·kg−1 i.v and reduced that of dorsal raphe 5-hydroxytryptaminergic neurones at doses >10-fold higher (minimal effective dose 8.2 µg·kg−1 i.v.). Both effects were reversed by the 5-HT1A antagonist (±)WAY100635. F15599 did not alter low frequency oscillations (∼1 Hz) in mPFC. In microdialysis studies, F15599 increased dopamine output in mPFC (an effect dependent on the activation of postsynaptic 5-HT1A receptors) with an ED50 of 30 µg·kg−1 i.p., whereas it reduced hippocampal 5-HT release (an effect dependent exclusively on 5-HT1A autoreceptor activation) with an ED50 of 240 µg·kg−1 i.p. Likewise, application of F15599 by reverse dialysis in mPFC increased dopamine output in a concentration-dependent manner. All neurochemical responses to F15599 were prevented by administration of (±)WAY100635., [Conclusions and implications]: These results indicate that systemic administration of F15599 preferentially activates postsynaptic 5-HT1A receptors in PFC rather than somatodendritic 5-HT1A autoreceptors. This regional selectivity distinguishes F15599 from previously developed 5-HT1A receptor agonists, which preferentially activate somatodendritic 5-HT1A autoreceptors, suggesting that F15599 may be particularly useful in the treatment of depression and of cognitive deficits in schizophrenia.

Recent discovery of the massive presence of gap junction couplings among neocortical FS (and LTS) interneurons poses serious questions about their collective dynamical behavior, and their possible cognitive roles. We present here the theoretical possibility that a class of neurons coupled by gap junctions may emerge spatio-temporal chaos itinerant among attractors in Milnor’s sense, which in turn organizes synchronous cell groups transiently. Some physiological observations from the neocortex, e.g., local field potential (LFP) data exhibiting transient synchrony may provide evidence. We suggest also possible role in the so-called binding problem.

Durch Kreuzkorrelation von ECoG- und EEG-Signalen hoher Bandbreite (10 - 400 Hz) mit dem Muster eines Amplituden - Zeit - Templates von 10 ms Dauer können Subpotentiale (SP) selektiert werden, die dem sogenannten ?local field potential? ähnlich sind.Diese Ähnlichkeit ergibt sich i. durch den Vergleich mit dem ermittelten Amplituden - Zeit - Template des SP. ii. durch den Vergleich mit der Lage der Quellstrukturen zur ableitenden Elektrode. Die SP - Modulanalyse liefert Potentialverteilung für jede untersuchte Elektrode. Diese ist stets in ein Nahfeld und Fernfelder organisiert, wobei die Polarität des Nahfeld der Polarität des Trigger- SP entspricht und das Fernfeld von entgegengesetzter Polarität ist. Diese Quellstrukturen sind um so kleiner, je geringer der Elektrodenabstand ist. iii. aus der Kohärenz von SP, die im Ableitfeld auftreten. Dafür wurde die SP- Zweikanalkopplungsanalyse entwickelt.Die einzelnen Schritte dieser SP - Methode, die sich aus der SP - event-, SP - Modul- und SP - Zweikanalkopplungsanalyse zusammensetzt, werden beschrieben und an einem Beispiel einer 30 kanaligen subduralen interiktalen ECoG - Ableitung eines Patienten mit fokaler Epilepsie unter drei verschiedenen Bedingungen (normales ECoG, ECoG mit spikes bzw. ECoG mit slow waves) sowie am Beispiel einer 30 kanaligen EEG-Ableitung eines Probanden unter drei verschiedenen kognitiven Anforderungen (relaxierte Wachheit, Kopfrechnen, beim Anhören eines Hörspiels) vergleichend demonstriert. Beide Beispiele sind repräsentativ für zwei größere Untersuchungsreihen., We obtained subpotentials (SP), similar to so called ?local field potentials? by application of cross - correlation on ECoG- and EEG- Signals with large band width (10 - 400 Hz) with the pattern of an amplitude-time-template with a duration of 10ms. This similarity is given by i. the comparison with obtained amplitude-time-template of the SP ii. the comparison with the position of source- structures to the deriving electrode. The potential distribution is given by the SP - moduleanalysis for each investigated electrode. This SP - module - analysis is always organised in a near- and in a far-field. The polarity of the near-field corresponds to the trigger-SP and the far-field to the opposite. The smaller the source-structure, the lower the distance of the electrodes iii.the coherence of SP in the deriving array The SP - method, consisting of SP - event, SP - module and SP ?two-channel-coupling -analysis? is described. The comparison between an example of an 30 channel subdural interictal derived ECoG of a patient, who was suffering from focal epilepsy, under three conditions (normal ECoG, ECoG with spikes and ECoG with slow-waves) and one of an 30 channel derived EEG of a candidate under three different cognitive demands (relaxed vigilance, doing mental arithmetic, listening to a radio serial) is demonstrated an discussed. Both examples are representatives for two extensive serials.