Building the Human Body: The Bionic Brain

By Kal Kaur

The Human Brain
A Groundbreaking Study – Mind Control
Neural Prosthetics
Research
Future Direction
References

The Human Brain

The human brain is mainly composed of cerebellum, brain stem, diencephalon and cerebral hemispheres. The cerebral cortex present in the uppermost part of the brain plays a key role in conscious behaviour. The diencephalon present in the centre of the forebrain includes thalamus, epithalamus and hypothalamus. The thalamus region groups the sensory inputs and regulates cortical arousal, memories and motor activities. The hypothalamus maintains body homeostasis by tweaking the autonomic nervous system. The brain stem is composed of grey matters covered by white matter fibers. The main parts of the stem are medulla oblongata, pons and midbrain. Blood pressure, heart rate, cranial nerves and respiratory rhythm are controlled by the nuclei of the medulla.

The function of cerebellum is to provide continuous coordinated movements by regulating contraction of skeletal muscles after receiving impulses from the sensory receptors, brain stem nuclei and cerebral motor cortex. Blood carried through the body via blood vessels performs the functions of supplying oxygen and nutrients absorbed from the digestive tract to the cells that assist in muscle contraction, carrying waste from the cells and facilitating gas exchange in the lungs. All these findings serve as a basis for the development of several novel approaches to resolve central nervous system-related problems such as restoration of memory loss, diagnosis of neural disorders like dystonia and Parkinson’s disease using neural prostheses.

A Groundbreaking Study – Mind Control

Messages are communicated from the brain to the body through neurons in the form of electrical impulses. Neurological disabilities are caused when damage to the central nervous system occurs. BrainGate has introduced a novel technology with an aim to improve the way of life for physically-disabled people by enabling them to communicate and interact. The BrainGate neural interface is equipped with a sensor and a brain signal analyzing device. The sensor is implanted on the brain for recording signals. The recorded signals are interpreted and then translated to provide the desirable movements.

This technology has allowed people with disabilities to control a computer using thought alone. The company has initiated research on making limb movements using the BrainGate neural interface to help people with physical disabilities. The company is indeed planning to extend its research on limb movements by designing a thought-controlled wheelchair. The following video demonstrates a breakthrough in application of the BrainGate neural interface system – a study funded by the National Institute of Health.

Neural Prosthetics

A neural prosthetic device can be best illustrated with a cochlear implant besides deep brain stimulation devices and a cardiac pacemaker. A modern cochlear implant is provided with an electrode assembly, a metal container and a speech processor. On the other hand, cardiac pacemakers consist of compact ceramic or metal containers. With the integration of digital signal processors into a cochlear implant, speech processing strategies and other parameters are now controlled using a software system. As the neural prostheses function inside the body of patients, the biological environment in which the neural prosthesis is present and the interactions between the implant and environment are collectively called as wetware. The wetware also constitutes other biological system elements like the brain, nerves, hormones and muscles.

Research

The transistor–neurons interface is an important breakthrough in the field of neural prostheses. Fromherz P et al (1991) carried out an experiment using multielectrode arrays stimulating the neurons. A silicon-chip was cultured with pre- and postsynaptic neurons of the snail Lymnaea. The silicon chip caused synaptic potentiation and non-invasively controls postsynaptic action potentials and activates the presynaptic cell by means of a capacitor beneath the neuron.

Neural interfaces (NIs) can be classified as either extracortical or intracortical NIs. The intracortical NIs are placed near the neurons and contacted with cortical parenchyma. These interfaces record single or multineuron spiking in addition to local field potentials. The extracortical NIs are located on an outer part of parenchyma which also detects electrical potentials. One best example of intracortical NIs is the BrainGate neural interface system that restores movements, communication and other physical disabilities of an individual by linking the cortex region to external devices. The intracortical NI acquires neural movement signals, decode and translate them for operating devices such as a computer or a prosthetic limb.

In contrast, a brain–computer interface/brain–machine interface (BCIs/BMIs) is similar to that of a biofeedback model except for a transform algorithm that converts neural activity into control parameters. These BMI models record the neural activities and convert them into signals using corresponding transform algorithms for controlling external devices. These algorithms enable the user to switch the device control based on the neural activity.

The BCIs employ signals obtained from a contralateral motor cortex (i.e., the part affected by stroke). As a result, BCIs prove less beneficial for hemiparetic patients. In order to make the implanted BCIs use the signals derived from unaffected ipsilateral cortex, it is necessary to identify the unique electrophysiological features of the cortex with respect to ipsilateral movements. Following this, Wisneski KJ et al (2008) studied the cortical physiology of six patients subjected to temporary intracranial electrode array placement.

Spectral changes corresponding to timing, location and frequency were detected using recorded ipsilateral electrocorticographic signals. The results proved that the ipsilateral movements are influenced by electrophysiological changes with low frequency spectra at specific locations. Hence, the findings showed that efficient device control can be accomplished through distinct electrophysiological features corresponding to ipsilateral movements.     

Future Direction

It is evident from the efforts carried out for the feasibility study of intracortical neural interfaces that technologies such as cardiac pacemakers would be suitable for neurological disorder management. Neural interface systems make use of extracranial and intracranial sensors to serve people with physical disability. Recent developments in these interface systems allow them to identify LFP patterns or abnormal spiking in damaged brains with the help of a high resolution sensor. The neural interfaces can also be potentially applied for detecting the transformation of normal electrical brain patterns to synchronous discharges that cause seizures.

The key role of brain plasticity in neural prostheses was reviewed by Fallon JB et al (2009). They concluded that wetware also has an ability to accomplish normal perception by identifying abnormal inputs. In addition, recent studies have revealed that the prosthetics can be directly controlled by applying simple algorithms on cortical activity instead of using complex algorithms for measuring the prosthetic control signal.

References

  • Fallon JB, Irvine D.R.F, Shepherd RK. Neural Prostheses and Brain Plasticity. Journal of Neural Engineering. Volume No.6, 2009
  • Chapter 2: Basic Anatomy and Physiology of the Human Brain. Published in: Schmidt F.E.W. Development of a Time-Resolved Optical Tomography System for Neonatal Brain Imaging. Med. Phys. 1999: 27, 1343: Pages 1–207.
  • Colicos M.A, Syed N.I. Neuronal networks and synaptic plasticity: understanding complex system dynamics by interfacing neurons with silicon technologies. The Journal of Experimental Biology. 2006; 209: 2312–2319.
  • Fetz E.E. Volitional control of neural activity: implications for brain–computer interfaces. The Journal of Physiology. 2007; 571–579.
  • Donoghue J.P, Nurmikko A, Black M, Hochberg L.R. Assistive technology and robotic control using motor cortex ensemble-based neural interface systems in humans with tetraplegia. The Journal of Physiology. 2007; 603–611.
  • Wisneski K.J, Anderson N, Schalk G, Smyth M. Unique Cortical Physiology Associated With Ipsilateral Hand Movements and Neuroprosthetic Implications. Stroke. 2008; 39: 3351–3359.
  • Fromherz, P., Offenhausser, A., Vetter, T. and Weis, J. A neuron-silicon junction: a Retzius cell of the leech on an insulated-gate field-effect transistor. Science. 1991; 252: 1290–1293.
Date Added: Nov 28, 2012 | Updated: Nov 28, 2012
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