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Biocomputing: what is so different about it?
NATURE has always been the major source of inspiration for science and scientists. Every invention of man kind has it prototype in the nature. Computer science also seeks inspiration from nature, specially from biological sciences.
Research in subjects, such as genetic algorithms, artificial neural networks and humanoids is going well and has seen major success. Other topics of interest are
• Theory of learning
• Neurosciences
• Bioinformatics and functional genomics
• Object detection/recognition
• Man machine interfaces
Neurosciences
The human brain is the most complex, sophisticated, powerful and central information-processing device known. For the study of brain’s complexities, experimental technologies of neurobiology, neuroscience and psychology are combined with the power of computational neuroscience and cognitive science. The human brain lies in the cranial cavity and is continuous with the spinal cord through the foramen magnum (a large opening in the anterior inferior part of the occipital bone between the cranial cavity and vertebral canal) is the central processing unit of the nervous system.
Some of the major areas of research in neurosciences are:
Molecular and cellular neuroscience: The study focuses on the development of neural connectivity, the molecular basis of behavior in simple neural circuits, synaptic plasticity, and neurochemistry.
Systems neuroscience: This field concerns with vision, movement, and endocrine regulation, with the goals of understanding the transduction and encoding of sensory stimuli; the organization, development, and plasticity of sensorimotor systems; the neural basis of cognition; and the effects of circulating compounds on brain composition and behavior.
Cognitive science: It includes experimental studies, linguistic theory, and computational modeling recruited to characterize the origin, acquisition, and processing of knowledge. Research focuses on visual perception and cognition, concepts and reasoning, and their development in children. Research on neurologically impaired patients is another important area of investigation.
Computation neuroscience: This emphasizes on the interdisciplinary study of the brain as an information processor and computing device. Research fields include robotics and the control of movement, vision, learning by neural networks, and knowledge-based perception and reasoning.
We will look into some of these research aspects and find what are the key regions of exploration.
Genetic & cellular neuroscience
It deals with a broad range of fundamental questions about genetic influences on mental processes and diseases as genome sequences become available. These sequences will make genetic manipulation of model organisms easier and more precise, which will enable detailed mapping of basic activities within and between brain cells. Technologies based on the sequences — including DNA arrays to detect expression of thousands of individual genes — will soon make it possible to determine the set of genes expressed in individual neurons in different brain structures and at different stages of development. Combining genetic, behavioural and brain imaging approaches will vastly improve diagnosis and treatment of illnesses that differ from each other in quite subtle ways.
On a larger scale, comparison of gene sequences and structures across organisms should reveal evolutionary relationships between specific brain regions of humans and other species, increasing the relevance of model systems. The ability to genetically manipulate specific regions of the central nervous system in animal models can greatly advance systems analysis of neural function.
Activity-dependent synaptic development: The various functions of the brain depend on how synapses form in response to other developmental activities. In particular, changes in biochemistry in the fetus affect how receptors take shape and regulate biochemical transmission. Disruption of activity-dependent changes due to perinatal disease, emotional neglect, or abnormal sensory environments during childhood can lead to lifelong damage to cognitive and sensory capabilities. By investigating the mechanisms that induce normal and abnormal synaptic development, it may be possible to selectively reactivate them, facilitating recovery from adult brain trauma and degeneration as well as diseases rooted in infancy.
Genetic structure
The development and normal functioning of the brain rely fundamentally on the structure of genes and how their expression is controlled. Understanding how neuronal genes are regulated may lead to better treatment of mental and neurological disorders, using drugs or hormones to correct underlying abnormalities. The sequencing of the human genome lays a foundation for understanding regulation of gene expression in brain cells and mapping of regulatory pathways. High throughput microarray technology that can survey known genetic sequences will be able to identify groups of genes whose expression levels characterize individual neurons when they are processing information within neural clusters.
Cognitive neuroscience
Latest research in imaging methods has made it possible to directly link ongoing brain function to human behaviour. This breakthrough is producing a wealth of new information about cognitive functions and should eventually uncover the roots of neurological and psychiatric diseases. It is now possible to visualize activity in localized regions of the human brain by using techniques such as functional magnetic resonance imaging (fMRI) and positron emission tomography (PET).
fRMI and the brain: Based on improvements in noninvasive technologies for displaying information about ongoing brain activity, cognitive neuroscience is creating maps that correlate behaviour and conscious reports with detailed brain functions. Experiments using imaging tools such as functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG) enable researchers to measure changes in brain activity during awake behaviour at varying temporal and spatial resolutions, from monitoring small neural clusters to large brain regions. The development of cognitive neuroscience is partly driven by attempts to increase imaging resolution, with the long-term goal of measuring single neurons over the course of milliseconds.
Computational neuroscience
Deals with the complexities and working of brain, which spans all levels of organization, from genes to channels to individual cells to networks of neurons to high brain functions. Computational neuroscience provides theoretical and computational tools that transcend many different levels of organization. Its approach is expanding into conventional neuroscience laboratories as the need for comprehensive analysis and interpretation of complex experimental data becomes increasingly difficult and important. Computational neuroscience has given specially important insight into higher visual activities.
Studying how the brain learns to recognize and categorize visual objects is helping to understand the circuitry of the visual cortex as well as to design machines that learn from experience. In addition to mapping the pathways and physiological processes underlying visual learning, these studies will lead to improved diagnosis of various brain disorders and to the development of visual prostheses.
Perception: The human brain has the remarkable capacity to perform the computationally difficult task of recognizing relevant objects in complex, continuously changing environment. It is still not completely ascertained as to how this is accomplished by any of the brain’s sensory systems.
From a computational viewpoint, the key problem solved by the brain is the extraction of object identity regardless of object position, size, view, and illumination, or the presence of clutter (for instance, noise or distractor objects). One hypothesis under study is that the brain solves this problem by transforming the pixel-based images of the world acquired by arrays of sensory receptors into high-level neuronal representations, or “tokens” of objects. For instance, in the visual system, those pixel-based images are gathered by the retina, while in the somatosensory (touch) system, they are gathered by arrays of mechanoreceptors on the surface of the skin, for instance, the finger pads).
Research at the MIT suggests that the pixel-based, retinal images are rapidly transformed into high-level neuronal object representations in the brain’s temporal lobe. For example, in both humans and monkeys, restricted temporal lobe lesions can specifically disrupt some types of object recognition (for instance, faces), while leaving other visual functions intact. Moreover, human functional MR imaging studies show that specific regions of the temporal lobe are selectively activated during the recognition of faces, places, and even body parts.
Motor control and learning
One of the central problems in systems and computational neuroscience is how the central nervous creates and updates internal representation of limb dynamics to manage complex, programmed movements under changing environmental conditions. The solutions should explain a wide variety of human behaviours, as well as forming the basis for treatments of diseases, such as strokes, spinal chord injuries, and various motor learning disorders. Recent studies have provided insight into how internal representations are built in the central nervous system and how motor memories are altered during learning.
Evidence suggests that internal representations form by combining modular primitives in the spinal cord as well as other building blocks in higher brain structures. Experimental studies on spinalized frogs, rats, and cats have shown that the premotor circuitry within the spinal cord is organized into a set of discrete modules. When each module is activated, a specific force field is evoked.
Simultaneous activation of multiple modules results in a vectorial combination of the fields. Other studies have shown that motor memories change over time by consolidating memories of learned movements, each of which initially exists in a vulnerable state.
Studies and researches are underway at various institutes and universities, such as MIT, Stanford University, Cardiff University, McGovern Institute and others with emphasis on determining the actual working and programming of the human nervous system so as to build efficient systems that imitate the behavior of biological systems which can help in study, diagnosis and treatment of illnesses that are due to nervous disorders. On the other hand it also helps in building machines that behave more like natural neural systems.
Imran Khan is a graduate in computer sciences from the University of Karachi; Kanwal Arif is a fourth year MBBS student at Hamdard College Of Medicine
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