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Aziz, T. Z.

Publications and source records attributed to Aziz, T. Z..

5 recordsLinked to original sources

Gait-phase modulates alpha and beta oscillations in the pedunculopontine nucleus

BackgroudThe pedunculopontine nucleus (PPN) is a reticular collection of neurons at the junction of the midbrain and pons, playing an important role in modulating posture and locomotion. Deep brain stimulation of the PPN has been proposed as an emerging treatment for patients with Parkinsons disease (PD) or multiple system atrophy (MSA) suffering gait-related atypical parkinsonian syndromes. ObjectiveIn this study, we investigated PPN activities during gait to better understand its functional role in locomotion. Specifically, we investigated whether PPN activity is rhythmically modulated during locomotion. MethodsPPN local field potential (LFP) activities were recorded from PD or MSA patients suffering from gait difficulties during stepping in place or free walking. Simultaneous measurements from force plates or accelerometers were used to determine the phase within each gait cycle at each time point. ResultsOur results showed that activities in the alpha and beta frequency bands in the PPN LFPs were rhythmically modulated by the gait phase within gait cycles, with a higher modulation index when the stepping rhythm was more regular. Meanwhile, the PPN-cortical coherence was most prominent in the alpha band. Both gait-phase related modulation in the alpha/beta power and the PPN-cortical coherence in the alpha frequency band were spatially specific to the PPN and did not extend to surrounding regions. ConclusionsThese results raise the possibility that alternating PPN stimulation in tandem with the gait rhythm may be more beneficial for gait control than continuous stimulation, although this remains to be established in future studies.

neuroscience↗

DyNeuMo Mk-1: A Fully-Implantable, Motion-Adaptive Neurostimulator with Configurable Response Algorithms

There is growing interest in using adaptive neuro-modulation to provide a more personalized therapy experience that might improve patient outcomes. Current implant technology, however, can be limited in its adaptive algorithm capability. To enable exploration of adaptive algorithms with chronic implants, we designed and validated the Picostim DyNeuMo Mk-1 (DyNeuMo Mk-1 for short), a fully-implantable, adaptive research stimulator that titrates stimulation based on circadian rhythms (e.g. sleep, wake) and the patients movement state (e.g. posture, activity, shock, free-fall). The design leverages off-the-shelf consumer technology that provides inertial sensing with low-power, high reliability, and relatively modest cost. The DyNeuMo Mk-1 system was designed, manufactured and verified using ISO 13485 design controls, including ISO 14971 risk management techniques to ensure patient safety, while enabling novel algorithms. The system was validated for an intended use case in movement disorders under an emergency-device authorization from the Medicines and Healthcare Products Regulatory Agency (MHRA). The algorithm configurability and expanded stimulation parameter space allows for a number of applications to be explored in both central and peripheral applications. Intended applications include adaptive stimulation for movement disorders, synchronizing stimulation with circadian patterns, and reacting to transient inertial events such as posture changes, general activity, and walking. With appropriate design controls in place, first-in-human research trials are now being prepared to explore the utility of automated motion-adaptive algorithms.

bioengineering↗

Basal ganglia high-frequency activity is co-modulated with the phase of motor cortical beta and shifted between the subthalamic nucleus and the internal pallidum during sustained motor control

Beta oscillations are readily observed in motor cortex and the basal ganglia, but to which extent they are functionally relevant is unclear. To understand how activity transfer between different nodes of the cortico-basal ganglia network is affected by cortical beta oscillations in different behavioural conditions, we recorded local field potentials and electroencephalography (EEG) activity in a low-force motor control task and during rest in Parkinsons patients undergoing deep brain stimulation (DBS) surgery. The patients received DBS of either the subthalamic nucleus (STN) or the internal globus pallidus (GPi), which allowed us to investigate if STN and GPi broad-band high-frequency activity (HFA; >150 Hz) is co-modulated with the phase of motor cortical beta activity. We found significant modulation patterns in the STN and the GPi, which were inverted while patients performed the task, showing that GPi activity fluctuations likely are crafted by other inputs than the direct excitatory STN afferents. We also found that consistent STN modulation disappeared during rest, showing disengagement in this condition, while GPi modulation was maintained, again evidencing that beta-band activity fluctuations in the GPi can be relatively independent of those in the STN. The difference between HFA modulation patterns in the task and rest recordings suggests a potential functional role of beta phase-locked HFA modulation in controlling sustained contractions. Examination of HFA co-modulation patterns at different sites of the cortico-basal ganglia-thalamo-cortical network under different behavioural conditions may provide a tool with which to define the impact of beta synchronization on network communication.

neuroscience↗

Decoding voluntary movements and postural tremor based on thalamic LFPs for closed-loop stimulation for essential tremor

High frequency deep brain stimulation (DBS) targeting motor thalamus is an effective therapy for essential tremor (ET). However, conventional continuous stimulation may deliver unnecessary current to the brain since tremor mainly affects voluntary movements and sustained postures in ET. We recorded LFPs from the motor thalamus, surface electromyographic (EMG) signals and/or behavioural measurements in seven ET patients during temporary lead externalization after the first surgery for DBS when they performed different voluntary upper limb movements and in nine more patients during the surgery, when they were asked to lift their arms to trigger postural tremor. We show that both voluntary movements and postural tremor can be decoded based on features extracted from thalamic LFPs using a machine learning based binary classifier. This information can be used to close the loop for DBS so that stimulation could be delivered on demand, without the need for peripheral sensors or additional invasive electrodes.

neuroscience↗

Uncovering the underlying mechanisms and whole-brain dynamics of therapeutic deep brain stimulation for Parkinson’s disease

Deep brain stimulation (DBS) for Parkinsons disease is a highly effective treatment in controlling otherwise debilitating symptoms yet the underlying brain mechanisms are currently not well understood. We used whole-brain computational modeling to disclose the effects of DBS ON and OFF during collection of resting state fMRI in ten Parkinsons Disease patients. Specifically, we explored the local and global impact of DBS in creating asynchronous, stable or critical oscillatory conditions using a supercritical bifurcation model. We found that DBS shifts the global brain dynamics of patients nearer to that of healthy people by significantly changing the bifurcation parameters in brain regions implicated in Parkinsons Disease. We also found higher communicability and coherence brain measures during DBS ON compared to DBS OFF. Finally, by modeling stimulation we identified possible novel DBS targets. These results offer important insights into the underlying effects of DBS, which may in time offer a route to more efficacious treatments.

neuroscience↗