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Cognitive and behavioral processes are often accompanied by changes within well-defined frequency bands of the local field potential (LFP i.e., the voltage induced by neuronal activity). These changes are detectable in the frequency domain using the Fourier transform and are often interpreted as neuronal oscillations. However, aside some well-known exceptions, the processes underlying such changes are difficult to track in time, making their oscillatory nature hard to verify. In addition, many non-periodic neural processes can also have spectra that emphasize specific frequencies. Thus, the notion that spectral changes reflect oscillations is likely too restrictive. In this study, we use a simple yet versatile framework to understand the frequency spectra of neural recordings. Using simulations, we derive the Fourier spectra of periodic, quasi-periodic and non-periodic neural processes having diverse waveforms, illustrating how these attributes shape their spectral signatures. We then show how neural processes sum their energy in the local field potential in simulated and real-world recording scenarios. We find that the spectral power of neural processes is essentially determined by two aspects: (1) the distribution of neural events in time and (2) the waveform of the voltage induced by single neural events. Taken together, this work guides the interpretation of the Fourier spectrum of neural recordings and indicates that power increases in specific frequency bands do not necessarily reflect periodic neural activity. [ABSTRACT FROM AUTHOR]

Cognitive and behavioral processes are often accompanied by changes within well-defined frequency bands of the local field potential (LFP i.e., the voltage induced by neuronal activity). These changes are detectable in the frequency domain using the Fourier transform and are often interpreted as neuronal oscillations. However, aside some well-known exceptions, the processes underlying such changes are difficult to track in time, making their oscillatory nature hard to verify. In addition, many non-periodic neural processes can also have spectra that emphasize specific frequencies. Thus, the notion that spectral changes reflect oscillations is likely too restrictive. In this study, we use a simple yet versatile framework to understand the frequency spectra of neural recordings. Using simulations, we derive the Fourier spectra of periodic, quasi-periodic and non-periodic neural processes having diverse waveforms, illustrating how these attributes shape their spectral signatures. We then show how neural processes sum their energy in the local field potential in simulated and real-world recording scenarios. We find that the spectral power of neural processes is essentially determined by two aspects: (1) the distribution of neural events in time and (2) the waveform of the voltage induced by single neural events. Taken together, this work guides the interpretation of the Fourier spectrum of neural recordings and indicates that power increases in specific frequency bands do not necessarily reflect periodic neural activity.

Basal ganglia dysfunction is implicated in movement disorders including Parkinson Disease, dystonia, and choreiform disorders. Contradicting standard “rate models” of basal ganglia-thalamic interactions, internal pallidotomy improves both hypo- and hyper-kinetic movement disorders. This “paradox of stereotaxic surgery” was recognized shortly after rate models were developed, and is underscored by the outcomes of deep brain stimulation (DBS) for movement disorders. Despite strong evidence that DBS activates local axons, the clinical effects of lesions and DBS are nearly identical. These observations argue against standard models in which GABAergic basal ganglia output gates thalamic activity, and raise the question of how lesions and stimulation can have similar effects. These paradoxes may be resolved by considering thalamocortical loops as primary drivers of motor output. Rather than suppressing or releasing cortex via motor thalamus, the basal ganglia may modulate the timing of thalamic perturbations to cortical activity. Motor cortex exhibits rotational dynamics during movement, allowing the same thalamocortical perturbation to affect motor output differently depending on its timing with respect to the rotational cycle. We review classic and recent studies of basal ganglia, thalamic, and cortical physiology to propose a revised model of basal ganglia-thalamocortical function with implications for basic physiology and neuromodulation.

Since its first experimental signatures, the so called “critical brain hypothesis” has been extensively studied. Yet, its actual foundations remain elusive. According to a widely accepted teleological reasoning, the brain would be poised to a critical state to optimize the mapping of the noisy and ever changing real-world inputs, thus suggesting that primary sensory cortical areas should be critical. We investigated whether a single barrel column of the somatosensory cortex of the anesthetized rat displays a critical behavior. Neuronal avalanches were recorded across all cortical layers in terms of both multi-unit activities and population local field potentials, and their behavior during spontaneous activity compared to the one evoked by a controlled single whisker deflection. By applying a maximum likelihood statistical method based on timeseries undersampling to fit the avalanches distributions, we show that neuronal avalanches are power law distributed for both multi-unit activities and local field potentials during spontaneous activity, with exponents that are spread along a scaling line. Instead, after the tactile stimulus, activity switches to a transient across-layers synchronization mode that appears to dominate the cortical representation of the single sensory input.

Since its first experimental signatures, the so called "critical brain hypothesis" has been extensively studied. Yet, its actual foundations remain elusive. According to a widely accepted teleological reasoning, the brain would be poised to a critical state to optimize the mapping of the noisy and ever changing real-world inputs, thus suggesting that primary sensory cortical areas should be critical. We investigated whether a single barrel column of the somatosensory cortex of the anesthetized rat displays a critical behavior. Neuronal avalanches were recorded across all cortical layers in terms of both multi-unit activities and population local field potentials, and their behavior during spontaneous activity compared to the one evoked by a controlled single whisker deflection. By applying a maximum likelihood statistical method based on timeseries undersampling to fit the avalanches distributions, we show that neuronal avalanches are power law distributed for both multi-unit activities and local field potentials during spontaneous activity, with exponents that are spread along a scaling line. Instead, after the tactile stimulus, activity switches to a transient across-layers synchronization mode that appears to dominate the cortical representation of the single sensory input. [ABSTRACT FROM AUTHOR]

Basal ganglia dysfunction is implicated in movement disorders including Parkinson Disease, dystonia, and choreiform disorders. Contradicting standard "rate models" of basal ganglia-thalamic interactions, internal pallidotomy improves both hypo- and hyper-kinetic movement disorders. This "paradox of stereotaxic surgery" was recognized shortly after rate models were developed, and is underscored by the outcomes of deep brain stimulation (DBS) for movement disorders. Despite strong evidence that DBS activates local axons, the clinical effects of lesions and DBS are nearly identical. These observations argue against standard models in which GABAergic basal ganglia output gates thalamic activity, and raise the question of how lesions and stimulation can have similar effects. These paradoxes may be resolved by considering thalamocortical loops as primary drivers of motor output. Rather than suppressing or releasing cortex via motor thalamus, the basal ganglia may modulate the timing of thalamic perturbations to cortical activity. Motor cortex exhibits rotational dynamics during movement, allowing the same thalamocortical perturbation to affect motor output differently depending on its timing with respect to the rotational cycle. We review classic and recent studies of basal ganglia, thalamic, and cortical physiology to propose a revised model of basal ganglia-thalamocortical function with implications for basic physiology and neuromodulation. [ABSTRACT FROM AUTHOR]

When analyzing neural data it is important to consider the limitations of the particular experimental setup. An enduring issue in the context of electrophysiology is the presence of common signals. For example a non-silent reference electrode adds a common signal across all recorded data and this adversely affects functional and effective connectivity analysis. To address the common signals problem, a number of methods have been proposed, but relatively few detailed investigations have been carried out. As a result, our understanding of how common signals affect neural connectivity estimation is incomplete. For example, little is known about recording preparations involving high spatial-resolution electrodes, used in linear array recordings. We address this gap through a combination of theoretical review, simulations, and empirical analysis of local field potentials recorded from the brains of fruit flies. We demonstrate how a framework that jointly analyzes power, coherence, and quantities based on Granger causality reveals the presence of common signals. We further show that subtracting spatially adjacent signals (bipolar derivations) largely removes the effects of the common signals. However, in some special cases this operation itself introduces a common signal. We also show that Granger causality is adversely affected by common signals and that a quantity referred to as “instantaneous interaction” is increased in the presence of common signals. The theoretical review, simulation, and empirical analysis we present can readily be adapted by others to investigate the nature of the common signals in their data. Our contributions improve our understanding of how common signals affect power, coherence, and Granger causality and will help reduce the misinterpretation of functional and effective connectivity analysis.

When analyzing neural data it is important to consider the limitations of the particular experimental setup. An enduring issue in the context of electrophysiology is the presence of common signals. For example a non-silent reference electrode adds a common signal across all recorded data and this adversely affects functional and effective connectivity analysis. To address the common signals problem, a number of methods have been proposed, but relatively few detailed investigations have been carried out. As a result, our understanding of how common signals affect neural connectivity estimation is incomplete. For example, little is known about recording preparations involving high spatial-resolution electrodes, used in linear array recordings. We address this gap through a combination of theoretical review, simulations, and empirical analysis of local field potentials recorded from the brains of fruit flies. We demonstrate how a framework that jointly analyzes power, coherence, and quantities based on Granger causality reveals the presence of common signals. We further show that subtracting spatially adjacent signals (bipolar derivations) largely removes the effects of the common signals. However, in some special cases this operation itself introduces a common signal. We also show that Granger causality is adversely affected by common signals and that a quantity referred to as “instantaneous interaction” is increased in the presence of common signals. The theoretical review, simulation, and empirical analysis we present can readily be adapted by others to investigate the nature of the common signals in their data. Our contributions improve our understanding of how common signals affect power, coherence, and Granger causality and will help reduce the misinterpretation of functional and effective connectivity analysis. [ABSTRACT FROM AUTHOR]

The electrochemical processes that underlie neural function manifest themselves in ceaseless spatial and temporal fluctuations in the extracellular electric field. The local field potential (LFP), used to study neural interactions during various brain states, is regarded as an epiphenomenon of coordinated neural activity. Yet the extracellular field activity feeds back onto the electrical potential across the neuronal membrane via ephaptic coupling (Jefferys et al, Physiol Rev, 1995). The extent to which such ephaptic coupling alters the functioning of individual neurons and neural assemblies under physiological conditions has remained largely speculative despite recent advances (Ozen et al, JNeurosci, 2010; Fröhlich & McCormick, Neuron, 2010, Anastassiou et al, JNeurosci, 2010). To address this question we use a 12-pipette setup that allows independent positioning of each pipette under visual control with μm accuracy, with the flexibility of using an arbitrary number of these as patching, extracellularly stimulating or extracellular recording pipettes only a few μm away from the cell body of patched neurons (Anastassiou et al, Nat Neurosci, 2011). We stimulated in rat somatosensory cortical slices a variety of layer 5 neural types and recorded inside and outside their cell bodies while pharmacologically silencing synaptic transmission. Pyramidal cells couple to the extracellular field distinctly different from interneurons. Ephaptic coupling strength depends both on the field strength (as measured at the neuron soma) as well as the spike-history of neurons. In particular, we find that ephaptic coupling strength depends both on the field strength (as measured at the cell body) as well as the spike-history of neurons. How do such effects manifest themselves in vivo? We address this question through detailed large-scale simulations from thousands of biophysically realistic and interconnected neurons (Reimann, Anastassiou et al, Neuron, 2013) emulating circuit activity. The simulations allow us to examine ephaptic coupling and dissociate between the feedforward (from membrane currents to LFP) and feedback (from LFPs to membrane voltage via ephapic coupling) effect in unprecedented detail. Our results support the notion that ephaptic coupling to endogenous electric fields in the brain may crucially impact neural communication. We hypothesize the functional role of such coupling in various brain states, for example, during visual processing (Anastassiou, Encyclopedia for Computational Neuroscience, Springer, 2014).

EEG gamma band oscillations have been proposed to account for the neural synchronization crucial for perceptual integration. While increased gamma power and synchronization is generally observed during cognitive tasks performed during wake, several studies have additionally reported increased gamma power during sleep or anesthesia, raising questions about the characteristics of gamma oscillation during impaired consciousness and its role in conscious processing. Phase-amplitude modulation has been observed between slow wave activity (SWA, 0.5–4 Hz) and gamma oscillations during ketamine/xylazine anesthesia or sleep, showing increased gamma activity corresponding to the depolarized (ON) state of SWA. Here we divided gamma activity into its ON and OFF (hyperpolarized) state components based on the phase of SWA induced by ketamine/xylazine anesthesia and compared their power and synchrony with wake state levels in mice. We further investigated the state-dependent changes in both gamma power and synchrony across primary motor and primary somatosensory cortical regions and their interconnected thalamic regions throughout anesthesia and recovery. As observed previously, gamma power was as high as during wake specifically during the ON state of SWA. However, the synchrony of this gamma activity between somatosensory-motor cortical regions was significantly reduced compared to the baseline wake state. In addition, the somatosensory-motor cortical synchrony of gamma oscillations was reduced and restored in an anesthetic state-dependent manner, reflecting the changing depth of anesthesia. Our results provide evidence that during anesthesia changes in long-range information integration between cortical regions might be more critical for changes in consciousness than changes in local gamma oscillatory power.

EEG gamma band oscillations have been proposed to account for the neural synchronization crucial for perceptual integration. While increased gamma power and synchronization is generally observed during cognitive tasks performed during wake, several studies have additionally reported increased gamma power during sleep or anesthesia, raising questions about the characteristics of gamma oscillation during impaired consciousness and its role in conscious processing. Phase-amplitude modulation has been observed between slow wave activity (SWA, 0.5-4 Hz) and gamma oscillations during ketamine/xylazine anesthesia or sleep, showing increased gamma activity corresponding to the depolarized (ON) state of SWA. Here we divided gamma activity into its ON and OFF (hyperpolarized) state components based on the phase of SWA induced by ketamine/xylazine anesthesia and compared their power and synchrony with wake state levels in mice. We further investigated the state-dependent changes in both gamma power and synchrony across primary motor and primary somatosensory cortical regions and their interconnected thalamic regions throughout anesthesia and recovery. As observed previously, gamma power was as high as during wake specifically during the ON state of SWA. However, the synchrony of this gamma activity between somatosensory-motor cortical regions was significantly reduced compared to the baseline wake state. In addition, the somatosensory-motor cortical synchrony of gamma oscillations was reduced and restored in an anesthetic state-dependent manner, reflecting the changing depth of anesthesia. Our results provide evidence that during anesthesia changes in long-range information integration between cortical regions might be more critical for changes in consciousness than changes in local gamma oscillatory power.