Ledochowitsch P, Koralek A C, Moses D, Carmena J M, Maharbiz M M
Annu Int Conf IEEE Eng Med Biol Soc. 2013;2013:5622-5. doi: 10.1109/EMBC.2013.6610825.
Volitional control of neural activity lies at the heart of the Brain-Machine Interface (BMI) paradigm. In this work we investigated if subdural field potentials recorded by electrodes < 1mm apart can be decoupled through closed-loop BMI learning. To this end, we fabricated custom, flexible microelectrode arrays with 200 µm electrode pitch and increased the effective electrode area by electrodeposition of platinum black to reduce thermal noise. We have chronically implanted these arrays subdurally over primary motor cortex (M1) of 5 male Long-Evans Rats and monitored the electrochemical electrode impedance in vivo to assess the stability of these neural interfaces. We successfully trained the rodents to perform a one-dimensional center-out task using closed-loop brain control to adjust the pitch of an auditory cursor by differentially modulating high gamma (70-110 Hz) power on pairs of surface microelectrodes that were separated by less than 1 mm.
神经活动的自主控制是脑机接口（BMI）范式的核心。在这项工作中，我们研究了间距小于1毫米的电极记录的硬膜下场电位是否可以通过闭环BMI学习进行解耦。为此，我们制作了定制的、电极间距为200 µm的柔性微电极阵列，并通过铂黑电沉积增加有效电极面积以降低热噪声。我们将这些阵列长期植入5只雄性Long-Evans大鼠的初级运动皮层（M1）硬膜下，并在体内监测电化学电极阻抗，以评估这些神经接口的稳定性。我们成功训练啮齿动物使用闭环脑控制执行一维中心外任务，通过差异调制间距小于1毫米的成对表面微电极上的高伽马（70-110 Hz）功率来调整听觉光标的间距。
