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This research aims to design a hardware optimized machine learning based Depth of Anesthesia (DOA) measurement framework for mice and its FPGA implementation.Electroencephalography or EEG signal is acquired from 16 mice in the Neural Interface Research (NIR) Laboratory of the City University of Hong Kong. We present a logistic regression based approach with mathematically uncomplicated feature extraction techniques for efficient hardware implementation to estimate the DOA.With the extraction of only two features, the proposed system can classify the state of consciousness with 94% accuracy for a 1 second EEG epoch, leading to a 100% accurate channel prediction after a 7 s run-time on average.Through performance evaluation and comparative study confirmed the efficacy of the prototype.DOA is the measure of consciousness to distinguish whether a patient is suitably anesthetized or not during a surgical procedure. Traditionally the DOA is estimated by checking biophysical responses of a patient during the surgery. However, the physical symptoms can be misleading for a decisive conclusion due to the patient's health condition or as a side-effect of anesthetic drugs. Recently, several neuroscientific research works are correlating the EEG signal with conscious states, which is likely to have less interference with the patient's medical condition. This research presents the first-of-its-kind hardware implemented automatic DOA computation system for mice.

Brain connectivity involves the structural, functional and effective communication between neurons across brain regions and is expressed in neuronal oscillations. Previous research has reported the evidence of two types of gamma oscillations namely the broadband gamma (30 Hz - 90 Hz) and narrowband gamma (55 Hz - 70 Hz) oscillations which have been implicated in excitatory and inhibitory network transmission. There is presently no systematic investigation of the relationship between electrical stimulation pulse width and narrow or broadband gamma oscillations in visual-deficient mice. In the current study, we set out to bridge this gap in knowledge by exploring the modulation of brain connectivity indices in broadband gamma and narrowband gamma oscillations in response to varying electrical stimulation pulse width in retinal degeneration (rd) mice. The results revealed that a low pulse width (0.5 ms/phase) strongly enhances coherence and directional connectivity of broadband and narrowband gamma oscillations in contra visual cortex and contra prefrontal cortex of rd mice. This study serves a crucial role in the design and utilisation of visual prostheses by contributing to the understanding of information transmission between different brain regions under retinal electrical stimulation in visual-deficit population.

Retinal degeneration (rd) is one of the leading causes of blindness in the modern world today. Various strategies including electrical stimulation are being researched for the restoration of partial or complete vision. Previous studies have demonstrated that the effectiveness of electrical stimulation in somatosensory, frontal and visual cortices is dependent on stimulation parameters including stimulation frequency and brain states. The aim of the study is to investigate the effect of applying a prolonged electrical stimulation on the eye of rd mice with various stimulation frequencies, in awake and anesthetized brain states. We recorded spontaneous electrocorticogram (ECoG) neural activity in prefrontal cortex and primary visual cortex in a mouse model of retinitis pigmentosa (RP) after prolonged (5-day) transcorneal electrical stimulation (pTES) at various frequencies (2, 10, and 20 Hz). We evaluated the absolute power and coherence of spontaneous ECoG neural activities in contralateral primary visual cortex (contra Vcx) and contralateral pre-frontal cortex (contra PFx). Under the awake state, the absolute power of theta, alpha and beta oscillations in contra Vcx, at 10 Hz stimulation, was higher than in the sham group. Under the anesthetized state, the absolute power of medium-, high-, and ultra-high gamma oscillations in the contra PFx, at 2 Hz stimulation, was higher than in the sham group. We also observed that the ultra-high gamma band coherence in contra Vcx-contra PFx was higher than in the sham group, with both 10 and 20 Hz stimulation frequencies. Our results showed that pTES modulates rd brain oscillations in a frequency and brain state-dependent manner. These findings suggest that non-invasive electrical stimulation of retina changes patterns of neural oscillations in the brain circuitry. This also provides a starting point for investigating the sustained effect of electrical stimulation of the retina to brain activities.

Transcorneal electrical stimulation (TES) has emerged as a non-invasive neuromodulation approach that exerts neuroprotection via diverse mechanisms, including neurotrophic, neuroplastic, anti-inflammatory, anti-apoptotic, anti-glutamatergic, and vasodilation mechanisms. Although current studies of TES have mainly focused on its applications in ophthalmology, several lines of evidence point towards its putative use in treating depression. Apart from stimulating visual-related structures and promoting visual restoration, TES has also been shown to activate brain regions that are involved in mood alterations and can induce antidepressant-like behaviour in animals. The beneficial effects of TES in depression were further supported by its shared mechanisms with FDA-approved antidepressant treatments, including its neuroprotective properties against apoptosis and inflammation, and its ability to enhance the neurotrophic expression. This article critically reviews the current findings on the neuroprotective effects of TES and provides evidence to support our hypothesis that TES possesses antidepressant effects.