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Although the electroencephalogram (EEG) activity of Autism Spectrum Disorder (ASD) has extremely complicated dynamics, the basic research on its dynamic modeling remains unexplored. This paper aims to investigate the mechanisms underlying EEG abnormalities in ASD from the perspective of dynamic modeling, and delve into the therapeutic principles of neuromodulation. First, by adjusting the average inhibitory synaptic gain and the average excitatory synaptic connection strength in the Wendling model, we reproduce clinical EEG characteristics of ASD, including Interictal Epileptiform Discharges (IEDs), increased relative power of the $\delta +𝜃$ band, decreased relative power of the $\alpha$ band, and reduced EEG complexity. This indicates that Excitation–Inhibition (EI) imbalance is potentially the trigger of abnormal EEG in ASD. Then, we demonstrate that both monophasic and biphasic repetitive Transcranial Magnetic Stimulation (rTMS) effectively control pathological discharges in ASD, with biphasic rTMS showing a reduced risk of over-control at the same frequency and intensity, consistent with clinical findings. Additionally, we show that Deep Brain Stimulation (DBS) plays a similar role to rTMS in the treatment of ASD, which proves the low-frequency DBS to be more effective in enhancing the complexity of brain activity, suggesting that DBS may hold promise as an innovative neuromodulation strategy for ASD. Our work helps to promote the development of dynamic modeling for ASD and to inspire therapeutic approaches for regulating the EI balance.

We report two cases of chronic therapeutic stimulation of epileptic foci localized in motor areas. Case 1 is an adolescent with supplementary motor area seizures whose intracranial recordings showed a right SMA focus. Case 2 is a female teenager with primary motor seizures originating in the right motor cortex in the hand area as shown by her intracranial recordings and cortical mapping. Both had apparently normal MRI. Chronic stimulation of the epileptic focus decreased the number of seizures more than 90% the seizure number while preserving motor function. None of the patients had side effects. Neuromodulation is proposed as a safe, efficient surgical alternative for motor seizure control.

Neuromodulation technologies such as vagus nerve stimulation and deep brain stimulation, have shown some efficacy in controlling seizures in medically intractable patients. However, inherent patient-to-patient variability of seizure disorders leads to a wide range of therapeutic efficacy. A patient specific approach to determining stimulation parameters may lead to increased therapeutic efficacy while minimizing stimulation energy and side effects. This paper presents a reinforcement learning algorithm that optimizes stimulation frequency for controlling seizures with minimum stimulation energy. We apply our method to a computational model called the epileptor. The epileptor model simulates inter-ictal and ictal local field potential data. In order to apply reinforcement learning to the Epileptor, we introduce a specialized reward function and state-space discretization. With the reward function and discretization fixed, we test the effectiveness of the temporal difference reinforcement learning algorithm (TD(0)). For periodic pulsatile stimulation, we derive a relation that describes, for any stimulation frequency, the minimal pulse amplitude required to suppress seizures. The TD(0) algorithm is able to identify parameters that control seizures quickly. Additionally, our results show that the TD(0) algorithm refines the stimulation frequency to minimize stimulation energy thereby converging to optimal parameters reliably. An advantage of the TD(0) algorithm is that it is adaptive so that the parameters necessary to control the seizures can change over time. We show that the algorithm can converge on the optimal solution in simulation with slow and fast inter-seizure intervals.

Transcranial direct current stimulation (tDCS) has been shown to create neuroplasticity in healthy and diseased populations. The control of stimulation duration by providing real-time brain state feedback using neuroimaging is a topic of great interest. This study presents the feasibility of a closed-loop modulation for the targeted functional network in the prefrontal cortex. We hypothesize that we cannot improve the brain state further after reaching a specific state during a stimulation therapy session. A high-definition tDCS of 1mA arranged in a ring configuration was applied at the targeted right prefrontal cortex of 15 healthy male subjects for 10min. Functional near-infrared spectroscopy was used to monitor hemoglobin chromophores during the stimulation period continuously. The correlation matrices obtained from filtered oxyhemoglobin were binarized to form subnetworks of short- and long-range connections. The connectivity in all subnetworks was analyzed individually using a new quantification measure of connectivity percentage based on the correlation matrix. The short-range network in the stimulated hemisphere showed increased connectivity in the initial stimulation phase. However, the increase in connection density reduced significantly after 6min of stimulation. The short-range network of the left hemisphere and the long-range network gradually increased throughout the stimulation period. The connectivity percentage measure showed a similar response with network theory parameters. The connectivity percentage and network theory metrics represent the brain state during the stimulation therapy. The results from the network theory metrics, including degree centrality, efficiency, and connection density, support our hypothesis and provide a guideline for feedback on the brain state. The proposed neuro-feedback scheme is feasible to control the stimulation duration to avoid overdosage.

Background: A small number of patients develop intractable peripheral nerve pain following injury or surgery to the upper limb that is refractory to pharmacological treatment. This study reports our results of using transcutaneous peripheral nerve stimulation (TPNS), a non-invasive form of neuromodulation, to treat this difficult problem.

Methods: Seventy-two patients were treated for intractable pain in the upper limb using this technique. Electrical current was delivered transcutaneously through a handheld probe, placed on the skin overlying the affected peripheral nerve proximal to the site of pain. Pain severity was determined before and immediately after treatment by subjective patient self-assessment using a visual analogue pain scale. Pre-post treatment changes in pain severity were analysed by Student's test for paired data. Outcome in respect of overall effectiveness of this treatment, was graded according to the maximum duration of pain relief achieved.

Results: Overall, TPNS reduced pain intensity from 8.4 (SD 1.6) before treatment to 4.2 (SD 3.5) immediately after treatment, a highly significant effect ($p<0.001$). The treatment achieved cure in 8/72 (11%) of our patients and a useful therapeutic outcome (pain relief ≥ 1 day) in 27/72 (38%). The treatment failed in 37/72 (51%).

Conclusions: TPNS warrants consideration as a therapy for neuropathic pain in the upper limb after drug treatment has failed and before offering surgery or spinal root stimulation.

Background: Traumatic neuromas are a result of abnormal neural regeneration after nerve injury. Neuropathic pain arising from neuroma can be debilitating.

Methods: This was a retrospective review of a consecutive series of patients who presented with a painful cutaneous neuroma secondary to direct trauma or surgery. The diagnosis was made by the presence of neuropathic symptoms in the dermatome of a cutaneous nerve and a positive Tinel sign. Local anaesthetic injection was performed for confirmation of diagnosis. Each patient was offered optimisation of medical therapy and physiotherapy for desensitisation. Outpatient neuromodulation was offered as an alternative to neuroma surgery. The primary aim of treatment was symptom reduction such that neuroma surgery was no longer required.

Results: This study included 50 patients with painful cutaneous neuromas. Surgery was the commonest cause. The most frequently injured nerves were superficial radial nerve, digital nerve and dorsal ulnar cutaneous nerve, together comprising over 60% of cases. After receiving neuromodulation, 18 (36%) patients experienced sufficient symptom relief and did not wish to pursue neuroma surgery.

Conclusions: Surgery is the commonest cause of a painful cutaneous neuroma. Following optimisation of pharmacotherapy and physiotherapy, neuromodulation may offer symptom relief such that neuroma surgery may be avoided in approximately one third of cases.

Autism has been viewed as a highly heritable neurobiological condition of mysterious but presumably genetic origin, which involves lifelong neurocognitive, perceptual and emotional deficits. This conceptual framing has led to a focus on searching for underlying genetic causes of differences in the autistic brain, particularly in anatomical structure, that are presumed to be hardwired into the system.

More recently, it is becoming clear that genes alone do not create autism. The more inclusive emerging view is that genes and environment interact to influence epigenetics, cell signaling and physiology. This formulation goes beyond the idea that a preconceptional or prenatal gene-environment interaction definitively causes a person's autism, and instead emphasizes that the interplay of all of these levels develops over time contingent upon exposures, experiences and lifestyle choices, and that the behaviors are actively produced by living cells that function differently, rather than simply being caused by static brain wiring that is different from the start.

From this vantage point it is important to look freshly at how we think about the brain, and what it is that the brain does to create autistic behaviors. A multi-scaled, whole-body, dynamical approach to the processes of signal generation in the brain and how these processes are shaped by ongoing dynamic interplays of multiple modulators offers previously unappreciated opportunities for improvement of brain function.