Sleep slow oscillation and plasticity

It is well documented that sleep contributes to memory consolidation and it is also accepted that long-term synaptic plasticity plays a critical role in memory formation. The mechanisms of this sleep-dependent memory formation are unclear. Two main hypotheses are proposed. According to the first one, synapses are potentiated during wake; and during sleep they are scaled back to become available for the learning tasks in the next day. The other hypothesis is that sleep slow oscillations potentiate synapses that were depressed due to persistent activities during the previous day and that potentiation provides physiological basis for memory consolidation. The objective of this review is to group information on whether cortical synapses are up-scaled or down-scaled during sleep. We conclude that the majority of cortical synapses are up-regulated by sleep slow oscillation

Modeling thalamocortical cell: impact of Ca2+ channel distribution and cell geometry on firing pattern

The influence of calcium channel distribution and geometry of the thalamocortical cell upon its tonic firing and the low threshold spike (LTS) generation was studied in a 3-compartment model, which represents soma, proximal and distal dendrites as well as in multi-compartment model using the morphology of a real reconstructed neuron. Using an uniform distribution of Ca2+ channels, we determined the minimal number of low threshold voltage-activated calcium channels and their permeability required for the onset of LTS in response to a hyperpolarizing current pulse. In the 3-compartment model, we found that the channel distribution influences the firing pattern only in the range of 3% below the threshold value of total T-channel density. In the multi-compartmental model, the LTS could be generated by only 64% of unequally distributed T-channels compared to the minimal number of equally distributed T-channels. For a given channel density and injected current, the tonic firing frequency was found to be inversely proportional to the size of the cell. However, when the Ca2+ channel density was elevated in soma or proximal dendrites, then the amplitude of LTS response and burst spike frequencies were determined by the ratio of total to threshold number of T-channels in the cell for a specific geometry

Precise long-range synchronization of activity and silence in neocortical neurons during slow-wave sleep

Slow-wave sleep is characterized by alternating periods of activity and silence in corticothalamic networks. Both activity and silence are stable network states, but the mechanisms of their alternation remain unknown. We show, using simultaneous multisite intracellular recordings in cats, that slow rhythm involves all neocortical neurons and that both activity and silence started almost synchronously in cells located up to 12 mm apart. Activity appeared predominantly at the area 5/7 border and spread in both anterior and posterior directions. The activity started earlier in fast-spiking cells and intrinsically bursting cells than in regular-spiking neurons. These results provide direct evidencefortwo mechanisms of active state generation: spread of activityfrom a localfocus and synchronization of weaker activity, originating at multiple locations. Surprisingly, onsets of silent states were synchronized even more precisely than the onsets of activity, showing no latency bias for location or cell type. This most intriguing finding exposes a major gap in understanding the nature of state alternation. We suggest that it is the synchronous termination of activity and occurrence of silent states of the neuronal network that makes the EEG picture during slow-wave sleep so characteristic. Synchronous onset of silence in distant neurons cannot rely exclusively on properties of individual cells and synapses, such as adaptation of neuronalfiring or synaptic depression; instead, it implies the existence of a network mechanism. Revealing this yet unknown large-scale mechanism, which switches network activity to silence, will aid our understanding of the origin of brain rhythms in normal function and pathology

Properties of slow oscillation during slow-wave sleep and anesthesia in cats

Deep anesthesia is commonly used as a model of slow-wave sleep (SWS). Ketamine–xylazine anesthesia reproduces the main features of sleep slow oscillation: slow, large-amplitude waves in field potential, which are generated by the alternation of hyperpolarized and depolarized states of cortical neurons. However, direct quantitative comparison of field potential and membrane potential fluctuations during natural sleep and anesthesia is lacking, so it remains unclear how well the properties of sleep slow oscillation are reproduced by the ketamine–xylazine anesthesia model. Here, we used field potential and intracellular recordings in different cortical areas in the cat to directly compare properties of slow oscillation during natural sleep and ketamine–xylazine anesthesia. During SWS cortical activity showed higher power in the slow/delta (0.1–4 Hz) and spindle (8–14 Hz) frequency range, whereas under anesthesia the power in the gamma band (30–100 Hz) was higher. During anesthesia, slow waves were more rhythmic and more synchronous across the cortex. Intracellular recordings revealed that silent states were longer and the amplitude of membrane potential around transition between active and silent states was bigger under anesthesia. Slow waves were mostly uniform across cortical areas under anesthesia, but in SWS, they were most pronounced in associative and visual areas but smaller and less regular in somatosensory and motor cortices. We conclude that, although the main features of the slow oscillation in sleep and anesthesia appear similar, multiple cellular and network features are differently expressed during natural SWS compared with ketamine–xylazine anesthesia

Multimodal Man-machine Interface and Virtual Reality for Assistive Medical Systems

The results of research the intelligence multimodal man-machine interface and virtual reality means for assistive medical systems including computers and mechatronic systems (robots) are discussed. The gesture translation for disability peoples, the learning-by-showing technology and virtual operating room with 3D visualization are presented in this report and were announced at International exhibition "Intelligent and Adaptive Robots–2005"

Age dependency of trauma-induced neocortical epileptogenesis

Trauma and brain infection are the primary sources of acquired epilepsy, which can occur at any age and may account for a high incidence of epilepsy in developing countries. We have explored the hypothesis that penetrating cortical wounds cause deafferentation of the neocortex, which triggers homeostatic plasticity and lead to epileptogenesis (Houweling et al., 2005). In partial deafferentation experiments of adult cats, acute seizures occurred in most preparations and chronic seizures occurred weeks to months after the operation in 65% of the animals (Nita et al., 2006, 2007; Nita and Timofeev, 2007). Similar deafferentation of young cats (age 8–12 months) led to some acute seizures, but we never observed chronic seizure activity even though there was enhanced slow-wave activity in the partially deafferented hemisphere during quiet wakefulness. This suggests that despite a major trauma, the homeostatic plasticity in young animals was able to restore normal levels of cortical excitability, but in fully adult cats the mechanisms underlying homeostatic plasticity may lead to an unstable cortical state. To test this hypothesis we made an undercut in the cortex of an elderly cat. After several weeks this animal developed seizure activity. These observations may lead to an intervention after brain trauma that prevents epileptogenesis from occurring in adults

Modeling of age-dependent epileptogenesis by differential homeostatic synaptic scaling

Homeostatic synaptic plasticity (HSP) has been implicated in the development of hyperexcitability and epileptic seizures following traumatic brain injury (TBI). Our in vivo experimental studies in cats revealed that the severity of TBI-mediated epileptogenesis depends on the age of the animal. To characterize mechanisms of these differences, we studied the properties of the TBI-induced epileptogenesis in a biophysically realistic cortical network model with dynamic ion concentrations. After deafferentation, which was induced by dissection of the afferent inputs, there was a reduction of the network activity and upregulation of excitatory connections leading to spontaneous spike-and-wave type seizures. When axonal sprouting was implemented, the seizure threshold increased in the model of young but not the older animals, which had slower or unidirectional homeostatic processes. Our study suggests that age-related changes in the HSP mechanisms are sufficient to explain the difference in the likelihood of seizure onset in young versus older animals

A wireless electro-optic platform for multimodal electrophysiology and optogenetics in freely moving rodents

This paper presents the design and the utilization of a wireless electro-optic platform to perform simultaneous multimodal electrophysiological recordings and optogenetic stimulation in freely moving rodents. The developed system can capture neural action potentials (AP), local field potentials (LFP) and electromyography (EMG) signals with up to 32 channels in parallel while providing four optical stimulation channels. The platform is using commercial off-the-shelf components (COTS) and a low-power digital field-programmable gate array (FPGA), to perform digital signal processing to digitally separate in real time the AP, LFP and EMG while performing signal detection and compression for mitigating wireless bandwidth and power consumption limitations. The different signal modalities collected on the 32 channels are time-multiplexed into a single data stream to decrease power consumption and optimize resource utilization. The data reduction strategy is based on signal processing and real-time data compression. Digital filtering, signal detection, and wavelet data compression are used inside the platform to separate the different electrophysiological signal modalities, namely the local field potentials (1–500 Hz), EMG (30–500 Hz), and the action potentials (300–5,000 Hz) and perform data reduction before transmitting the data. The platform achieves a measured data reduction ratio of 7.77 (for a firing rate of 50 AP/second) and weights 4.7 g with a 100-mAh battery, an on/off switch and a protective plastic enclosure. To validate the performance of the platform, we measured distinct electrophysiology signals and performed optogenetics stimulation in vivo in freely moving rondents. We recorded AP and LFP signals with the platform using a 16-microelectrode array implanted in the primary motor cortex of a Long Evans rat, both in anesthetized and freely moving conditions. EMG responses to optogenetic Channelrhodopsin-2 induced activation of motor cortex via optical fiber were also recorded in freely moving rodents

Origin of Active States in Local Neocortical Networks during Slow Sleep Oscillation

Slow-wave sleep is characterized by spontaneous alternations of activity and silence in corticothalamic networks, but the causes of transition from silence to activity remain unknown. We investigated local mechanisms underlying initiation of activity, using simultaneous multisite field potential, multiunit recordings, and intracellular recordings from 2 to 4 nearby neurons in naturally sleeping or anesthetized cats. We demonstrate that activity may start in any neuron or recording location, with tens of milliseconds delay in other cells and sites. Typically, however, activity originated at deep locations, then involved some superficial cells, but appeared later in the middle of the cortex. Neuronal firing was also found to begin, after the onset of active states, at depths that correspond to cortical layer V. These results support the hypothesis that switch from silence to activity is mediated by spontaneous synaptic events, whereby any neuron may become active first. Due to probabilistic nature of activity onset, the large pyramidal cells from deep cortical layers, which are equipped with the most numerous synaptic inputs and large projection fields, are best suited for switching the whole network into active state