Abstract: It has been noted that the power spectrum of intracortical local field potential (LFP) often scales as 1/f(-2). It is thought that LFP mostly represents the spiking-related neuronal activity such as synaptic currents and spikes in the vicinity of the recording electrode, but no 1/f(2) scaling is detected in the spike power. Although tissue filtering or modulation of spiking activity by UP and DOWN states could account for the observed LFP scaling, there is no consensus as to how it arises. We addressed this question by recording simultaneously LFP and single neurons ("single units") from multiple sites in somatosensory cortex of anesthetized rats. Single-unit data revealed the presence of periods of high activity, presumably corresponding to the "UP" states when the neuronal membrane potential is depolarized, and periods of no activity, the putative "DOWN" states when the membrane potential is close to resting. As expected, the LFP power scaled as 1/f(2) but no such scaling was found in the power spectrum of spiking activity. Our analysis showed that 1/f(2) scaling in the LFP power spectrum was largely generated by the steplike transitions between UP and DOWN states. The shape of the LFP signal during these transitions, but not the transition timing, was crucial to obtain the observed scaling. These transitions were probably induced by synchronous changes in the membrane potential across neurons. We conclude that a 1/f(2) scaling in the LFP power indicates the presence of steplike transitions in the LFP trace and says little about the statistical properties of the associated neuronal firing.
Abstract: Extracellular metal microelectrodes are widely used to record single neuron activity in vivo. However, their signal-to-noise ratio (SNR) is often far from optimal due to their high impedance value. It has been recently reported that carbon nanotube (CNT) coatings may decrease microelectrode impedance, thus improving their performance. To tease out the different contributions to SNR of CNT-coated microelectrodes we carried out impedance and noise spectroscopy measurements of platinum/tungsten microelectrodes coated with a polypyrrole-CNT composite. Neuronal signals were recorded in vivo from rat cortex by employing tetrodes with two recording sites coated with polypyrrole-CNT and the remaining two left untreated. We found that polypyrrole-CNT coating significantly reduced the microelectrode impedance at all neuronal signal frequencies (from 1 to 10 000 Hz) and induced a significant improvement of the SNR, up to fourfold on average, in the 150-1500 Hz frequency range, largely corresponding to the multiunit frequency band. An equivalent circuit, previously proposed for porous conducting polymer coatings, reproduced the impedance spectra of our coated electrodes but could not explain the frequency dependence of SNR improvement following polypyrrole-CNT coating. This implies that neither the neural signal amplitude, as recorded by a CNT-coated metal microelectrode, nor noise can be fully described by the equivalent circuit model we used here and suggests that a more detailed approach may be needed to better understand the signal propagation at the electrode-solution interface. Finally, the presence of significant noise components that are neither thermal nor electronic makes it difficult to establish a direct relationship between the actual electrode noise and the impedance spectra.
Abstract: Brain-Machine Interfaces (BMIs) are systems which mediate communication between brains and artificial devices. Their long term goal is to restore motor functions, and this ultimately demands the development of a new generation of bidirectional brain-machine interfaces establishing a two-way brain-world communication channel, by both decoding motor commands from neural activity and providing feedback to the brain by electrical stimulation. Taking inspiration from how the spinal cord of vertebrates mediates communication between the brain and the limbs, here we present a model of a bidirectional brain-machine interface that interacts with a dynamical system by generating a control policy in the form of a force field. In our model, bidirectional communication takes place via two elements: (a) a motor interface decoding activities recorded from a motor cortical area, and (b) a sensory interface encoding the state of the controlled device into electrical stimuli delivered to a somatosensory area. We propose a specific mathematical model of the sensory and motor interfaces guiding a point mass moving in a viscous medium, and we demonstrate its performance by testing it on realistically simulated neural responses.
Abstract: Brain-machine interfaces (BMIs) are mostly investigated as a means to provide paralyzed people with new communication channels with the external world. However, the communication between brain and artificial devices also offers a unique opportunity to study the dynamical properties of neural systems. This review focuses on bidirectional interfaces, which operate in two ways by translating neural signals into input commands for the device and the output of the device into neural stimuli. We discuss how bidirectional BMIs help investigating neural information processing and how neural dynamics may participate in the control of external devices. In this respect, a bidirectional BMI can be regarded as a fancy combination of neural recording and stimulation apparatus, connected via an artificial body. The artificial body can be designed in virtually infinite ways in order to observe different aspects of neural dynamics and to approximate desired control policies.
Abstract: Neurons extracted from specific areas of the Central Nervous System (CNS), such as the hippocampus, the cortex and the spinal cord, can be cultured in vitro and coupled with a micro-electrode array (MEA) for months. After a few days, neurons connect each other with functionally active synapses, forming a random network and displaying spontaneous electrophysiological activity. In spite of their simplified level of organization, they represent an useful framework to study general information processing properties and specific basic learning mechanisms in the nervous system. These experimental preparations show patterns of collective rhythmic activity characterized by burst and spike firing. The patterns of electrophysiological activity may change as a consequence of external stimulation (i.e., chemical and/or electrical inputs) and by partly modifying the "randomness" of the network architecture (i.e., confining neuronal sub-populations in clusters with micro-machined barriers). In particular we investigated how the spontaneous rhythmic and synchronous activity can be modulated or drastically changed by focal electrical stimulation, pharmacological manipulation and network segregation. Our results show that burst firing and global synchronization can be enhanced or reduced; and that the degree of synchronous activity in the network can be characterized by simple parameters such as cross-correlation on burst events.
Abstract: In vitro cultured neuronal networks coupled to microelectrode arrays (MEAs) constitute a valuable experimental model for studying changes in the neuronal dynamics at different stages of development. After a few days in culture, neurons start to connect each other with functionally active synapses, forming a random network and displaying spontaneous electrophysiological activity. The patterns of collective rhythmic activity change in time spontaneously during in vitro development. Such activity-dependent modifications play a key role in the maturation of the network and reflect changes in the synaptic efficacy, fact widely recognized as a cellular basis of learning, memory and developmental plasticity. Getting advantage from the possibilities offered by the MEAs, the aim of our study is to analyze and characterize the natural changes in dynamics of the electrophysiological activity at different ages of the culture, identifying peculiar steps of the spontaneous evolution of the network. The main finding is that between the second and the third week of culture, the network completely changes its electrophysiological patterns, both in terms of spiking and bursting activity and in terms of cross-correlation between pairs of active channels. Then the maturation process can be characterized by two main phases: modulation and shaping in the synaptic functional connectivity of the network (within the first and second week) and general moderate correlated activity, spread over the entire network, with connections properly formed and stabilized (within the fourth and fifth week).
Abstract: Two main features make microelectrode arrays (MEAs) a valuable tool for electrophysiological measurements under the perspective of pharmacological applications, namely: (i) they are non-invasive and permit, under appropriate conditions, to monitor the electrophysiological activity of neurons for a long period of time (i.e. from several hours up to months); (ii) they allow a multi-site recording (up to tens of channels). Thus, they should allow a high-throughput screening while reducing the need for animal experiments. In this paper, by taking advantages of these features, we analyze the changes in activity pattern induced by the treatment with specific substances, applied on dissociated neurons coming from the chick-embryo spinal cord. Following pioneering works by Gross and co-workers (see e.g. Gross and Kowalski, 1991. Neural Networks, Concepts, Application and Implementation, vol. 4. Prentice Hall, NJ, pp. 47-110; Gross et al., 1992. Sensors Actuators, 6, 1-8.), in this paper analysis of the drugs' effects (e.g. NBQX, CTZ, MK801) to the collective electrophysiological behavior of the neuronal network in terms of burst activity, will be presented. Data are simultaneously recorded from eight electrodes and besides variations induced by the drugs also the correlation between different channels (i.e. different area in the neural network) with respect to the chemical stimuli will be introduced (Bove et al., 1997. IEEE Trans. Biomed. Eng., 44, 964-977.). Cultured spinal neurons from the chick embryo were chosen as a neurobiological system for their relative simplicity and for their reproducible spontaneous electrophysiological behavior. It is well known that neuronal networks in the developing spinal cord are spontaneously active and that the presence of a significant and reproducible bursting activity is essential for the proper formation of muscles and joints (Chub and O'Donovan, 1998. J. Neurosci., 1, 294-306.). This fact, beside a natural variability among different biological preparations, allows a comparison also among different experimental session giving reliable results and envisaging a definition of a bioelectronic 'neuronal sensory system'.
