The isocortex of all mammals studied to date shows a progressive increase in the amount and continuity of background activity during early development. In humans the transition from a discontinuous (mostly silent, intermittently bursting) cortex to one that is continuously active is complete soon after birth and is a critical prognostic indicator in newborns. In the visual cortex of rodents this switch from discontinuous to continuous background activity occurs rapidly during the two days before eye-opening, driven by activity changes in relay thalamus. The factors that regulate the timing of continuity development, which enables mature visual processing, are unknown. Here we test the role of the retina, the primary input, in the development of continuous spontaneous activity in the visual system of mice using depth electrode recordings of cortical activity from enucleated mice in vivo. Bilateral enucleation at postnatal day (P)6, one week prior to the onset of continuous activity, acutely silences cortex, yet firing rates and early oscillations return to normal within two days and show a normal developmental trajectory through P12. Enucleated animals showed differences in silent period duration and continuity on P13 that resolved on P16, and an increase in low frequency power that did not. Our results show that the timing of cortical activity development is not determined by the major driving input to the system. Rather, homeostatic mechanisms in thalamocortex regulate firing rates and continuity even across periods of rapid maturation.
The isocortex of all mammals studied to date shows a progressive increase in the amount and continuity of background activity during early development. In humans the transition from a discontinuous (mostly silent, intermittently bursting) cortex to one that is continuously active is complete soon after birth and is a critical prognostic indicator. In the visual cortex of rodents this switch from discontinuous to continuous background activity occurs during the two days before eye-opening, driven by activity changes in relay thalamus. The factors that regulate the timing of continuity development, which enables mature visual processing, are unknown. Here we test the role of the retina, the primary input, in the development of continuous spontaneous activity in the visual cortex of mice using depth electrode recordings from Enucleated mice in vivo. Bilateral enucleation at postnatal day (P)6, one week prior to the onset of continuous activity, acutely silences cortex, yet firing rates and early oscillations return to normal within two days and show a normal developmental trajectory through P12. Enucleated animals showed differences in silent period duration and continuity on P13 that resolved on P16, and an increase in low frequency power that did not. Our results show that the timing of cortical activity development is not determined by the major driving input to the system. Rather, even during a period of rapid increase in firing rates and continuity, neural activity in the visual cortex is under homeostatic control that is largely robust to the loss of the primary input. SIGNIFICANCE STATEMENTUncovering the mechanistic underpinnings of EEG development is critical to increasing the diagnostic potential of this cheap and portable methodology. An important component of this maturation is the acquisition of activity that is continuous, i.e. lacking silent periods. Here we used background activity in the visual cortex of developing unanesthetized mice to show that the primary sensory input plays little role in the development of continuity and normal firing rates, which instead appear to be regulated by mechanism internal to thalamus and cortex. These findings suggest that damage to driving thalamic inputs will be difficult to detect by EEG, and point to the importance of firing rate homeostasis in regulating even early development.
Collision alert and avoidance systems (CAS) could help to minimize driver errors. They are instrumental as an advanced driver-assistance system (ADAS) when the vehicle is facing potential hazards. Developing effective ADAS/CAS, which provides alerts to the driver, requires a fundamental understanding of human sensory perception and response capabilities. This research explores the premise that external stimulation can effectively improve drivers’ reaction and response capabilities. Therefore this article proposes a light-emitting diode (LED)-based driver warning system to prevent potential collisions while evaluating novel signal processing algorithms to explore the correlation between driver brain signals and external visual stimulation. When the vehicle approaches emerging obstacles or potential hazards, an LED light box flashes to warn the driver through visual stimulation to avoid the collision through braking. Thirty (30) subjects completed a driving simulator experiment under different near-collision scenarios. The Steady-State Visually Evoked Potentials (SSVEP) of the drivers’ brain signals and their collision mitigation (control performance) data were analyzed to evaluate the LED warning system’s effectiveness. The results show that (1) The proposed modified canonical correlation analysis evaluation (CCA-EVA) algorithm can detect SSVEP responses with 4.68% higher accuracy than the Adaptive Kalman filter; (2) The proposed driver monitoring and alert system produce on average a 52% improvement in time to collision (TTC), 54% improvement in reaction distance (RD), and an overall 26% reduction in collision rate as compared to similar tests without the LED warning.
This article evaluates an M-order Adaptive Kalman filter analysis on Steady-State Visual Evoked Potentials (SSVEPs). This model is based on finding the original brain source signals from their combined observed EEG signals. At each time step, observed brain signals are filtered according to their ideal reference signals measured from 10, 11, 12 and 13 Hz LED stimuli. SSVEP response detection is based on maximum Signal to Noise Ratio (SNR) of the brain source signals. In each test, the average system accuracy is calculated with and without overlapped time-windows along with system Information Transfer Rate (ITR). The overall system accuracy and ITR are showing promising level of SSVEP detection for future online BCI systems.
Steady-State Visual Evoked Potential (SSVEP) Brain-Computer Interfaces (BCIs) are becoming more interesting with increases in demand for robust BCI systems with real-time control capability. This type of BCI is based on collecting the brain signals from visual cortex while the users' attention is toward an exogenous stimulus. Stimulus with constant frequency rate above 4 Hz evokes the SSVEPs. This research uses the data collected from 4 healthy subjects. Each subject participated in test sessions with 4 different LEDs, flickering at 10, 11, 12 and 13 Hz. A 10-order adaptive prioribased robust Gauss-Newton algorithm is adjusted to estimate the brain source signals. Finally, decision detection is based on the maximum Signal to Noise Ratio (SNR). Results are promising an effective method, which could be later developed for implementation of online BCI systems.
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