Introduction
Throughout history, the understanding of how the human body functions have remained the center of concern. Of particular interest is the knowledge of body cells which according to many, significantly explains process flows and interpretation of perceived and real information. In this regard, electrophysiological techniques have been developed to enhance the understanding of the electrical characteristics of cells and tissues in animals. Additionally, advances in these techniques have increased our understanding of neuronal multisensory integration. This essay gives an analysis of some of the electrophysiological techniques and how their advancements have transformed the manner in which human beings view and comprehend neuronal multisensory integration.
Electrophysiology
The understanding of how the brain orchestrates actions, perceptions and thoughts from the electrical dynamic of neurons is quite fascinating. The organization of the brain generally offers several patterns which are distinct at different levels ranging from interacting systems to synapses. In addressing these issues, physiologists are usually faced with the challenge of formulating methods that offer a short-term and spatial resolution for the activities of the neurons across networks (Puce & Perrett, 2003). Although there are several methods of finding these, there is always the need of translating collected data into neuronal spike trains format to understand how the brain controls behavior.
It is vital to understand that the existence of specific behavior in animals emerges as a result of the interaction between neuronal pools and neurons. Nevertheless, analyzing such processes can only be effective when bulky neurons are used in several regions of the brain. Current physiological techniques permit the recording of a high number of heavy apical dendrites. In these bulky tissues, there is a usually high level of neurons making their identification and isolation from a common site difficult (Puce & Perrett, 2003). This task can therefore be accomplished by making use of multiple recording sites like four or eight.
From a broader perspective, electrophysiology focuses on electrical phenomena which play a major role in animals. Membrane protein complexes through which voltage changes usually permit the flow of ions from one cell to another via permeable membranes (Giard & Besle, 2010). These channels are present in neuron membranes which constitute nerves, the brain, and the spinal column. Mechanisms of these channels further cause a shift of voltage across several cell membranes. Determination of such changes is essential in comprehending neuronal multisensory integration and is accomplished by applying several techniques some of which are discussed below:
Single-unit recording
Under this approach, the electrophysiological activity of a cell is measured and recorded using an electrode. The electrode is introduced in the brain of an animal to detect any electrical activity produced by neurons occurring adjacent to the end of the electrode (Avery, Raizen & Lockeryt, 1995). When a microelectrode is used, only the electrical activity of a single neuron is detected. This implies that the number of neurons analyzed for conductivity solely depends on the size of the tip of the electrode used. The activity recorded mainly consists of the current generated by fields that lie outside the cell. These recordings are however related to intracellular ones with differences in the magnitude of the signals.
The single-unit recording technique is essential in the understanding of how the brain of animals processes information. Many scholars who have researched on Single-unit recording of the visual cortex of animals have found factual information corresponding to visual stimuli generated using a single neuron. Notably, larger electrodes are used to record the activity that is generated by several neurons in the brain. This type of recording is referred to as multi-unit recording and is commonly used when carrying out investigations on conscious animals. From the recording, one is able to note the changes in potential differences when the animal is functioning normally (Schiller & Stryker, 1972). Recordings from such electrodes have been found to be useful especially when identifying the number of cells and the identity of every spike as they originate from different cells. It is scientifically referred to as spike sorting and is common when dealing with cells whose spikes are distinctively known. In cases where the electrode tip is magnified, potential differences of individual neurons cannot be established although a field potential would be recorded for the numerous cells present. The single-unit recording also has its application in human medicine and is applied prior to or after brain surgery. It helps the performing surgeon to identify the exact to be removed from the brain during surgery (Avery, Raizen & Lockeryt, 1995).
Patch-clamp
This technology allows physiologists to study ion channels in the laboratory. It was developed by two scientists, Bert Sakmann and Erwin Neher in 1970s who won the Nobel Peace Prize in the year 1991. Patch clamp makes use of the patch-clamp microelectrode which is simply a micropipette that has a relatively larger diameter (Walz, Boulton & Baker, 2002). Its mechanism involves the placement of the microelectrode next to the cell to be studied before suction is applied through the electrode. As a result of the suction, the cell membrane is drawn to the tip of the electrode, forming high resistance. This can incorporated when studying the potential of ion channels occurring in the membrane (Avery, Raizen & Lockeryt, 1995). Although this technique can be applied to many cells, it is common in muscle fibers, neurons, pancreatic beta cells among others.
Electrophysiology and brain imaging
In general, social primates derive a lot of stimuli from movement of bodies and faces which are of significant interest in understanding neuronal multisensory integration. From data recorded through physiological techniques, it has been found that privates highly depend on observable behaviors of each other which get integrated in their normal social life (Versace, et al., 2009). On the hand, the ability of human beings to identify and interpret motions has far reaching impact besides the need to successfully survive and interact with one another. Minus this ability, interactions and recreational activities among human beings would be impossible and minimal. It therefore suffices to mention that advances which have been realized in physiology are core ingredients in not only for study purposes but also in augmenting the understanding of neuronal multisensory integration. Through this integration, human beings are able to interpret certain images sent to the brain when observed within the environment (Besle, Fort, & Giard, 2004).
Cross-modal integration
This technique focuses on the characteristics of the object in question as opposed to its position and orientation in space. Based on this approach, there are studies which have been carried out to analyze where and how animal brain interprets cross-modal properties of an object. These studies are broadly categorized as those with language stimuli and non linguistic stimuli. They have heard impact on the overall understanding of the neural multisensory integration especially in analyzing features of a given object being interpreted by the brain. Thus researchers develop evidence which clearly illustrates the role of Superior Temporal Sulcus, STS in analyzing audiovisual communication and general language signals (Stein et al., 2009). This concurs with continuous imaging of data around the world recognizing the role of STS in communication signals. In cases where cross-modal interactions exist fully, amplifications may be transmitted through back-projections emanating from areas considered to be of higher processing like STS.
From different physiological techniques which have been applied in understanding of multisensory integration, it is clear that networks within the brain play a momentous role in cross-modal matching as compared to any other area. Additionally, different elements of these networks are physiologically differentiated for the purpose of analyzing varying cross-modal information. With current advancement in technology, it is worth noting that the functions of these compartments are becoming more distinct and well defined. For instance, STS is essential during the integration of intricate features of the information perceived through audiovisual communication (Puce & Perrett, 2003). On the other hand, synthesizing of cross-modal spatial signals is mainly coordinated by the IPS. It also mediates cross-modal connections that are being analyzed.
Multisensory integration
Three main functions of the brain are encoding, decoding and interpreting information collected within ones vicinity (Stein et al., 2009). Due to this noble task, the brain requires a well established neuron circuitry. This has led to a realization of paramount development of sensory organs in specific regions of the body. There are countless benefits associated with having multiple senses for optimal image identification and interpretation when this information is relayed for action to be launched. However, the ability to combine the origin of information makes interpretation faster than relying on individual contributors transmitting information to the brain. This interaction of several senses and combining of interpreted information is what is described as multisensory integration (Stein & Stanford, 2008). Through cross-modal stimulus, it is possible to understand the impact of several impulses together with their individual effectiveness. How does this result? Multisensory integration depends on the ultimate response of the neuron based on its enhancement or depression in detecting a viable response towards an existing signal. Additionally, the ability of multisensory integration to enhance detection of a particular event affects the speed at which reactions are generated.
Notably, the brain has the functional ability of altering reactions especially when information is collected from a variety of senses. Through the development of several physiological techniques some of which have been discussed above, there is immense information which synthesizes neuronal multisensory integration. This can be described as an innovative development that continues to address problems regarding coding, decoding and interpretation of information (Stein et al., 2009). In interpreting data collected from multisensory response, it is possible to analyze characteristics of individual neurons and the nature of the stimuli against which the evaluation was done.
Inverse effectiveness
In early developments of multisensory integration, the magnitude of the response was always compared to the characteristics of the stimuli generated. However, stimuli that triggered higher responses elicited weaker levels of multisensory enhancement (Stein et al., 2009). Nonetheless, an opposite situation was observed in multisensory depression. As a result, the two findings had unique trends and called for independent analysis. The two were triggered by different stimulations by enhancement and depression. This led to the exploration of individual neurons through alteration of their efficiency and quantifying the multisensory product.
This principle has tremendously been used in analyzing data trends during physiological experiments around the world. Apart from its application, inverse effectiveness has turned out to be effective in comprehensively synthesizing individual neurons against their individual properties within a given period of time of multisensory responses (Stein et al., 2009). There is lot of information and data which has been collected to describe this principle that transformed physiological approach towards neuronal multisensory integration. In other cases, the principle has been employed to generate comparisons emanating from the use of different unisensory differences (Stein & Stanford, 2008).
The application of this technique has become common in explaining differences in populations especially when individual neurons are being tasted against their unique electrical properties. Of significance is the extent to which physiologists have benefited from this approach. It is however important to put into consideration a number of issues which may undermine the efficacy of such experiments and analysis. For instance, response properties may vary because of different neuron characteristics.
Conclusion
From the above analysis, it is evident that several techniques used in physiology have played a pivotal role in advancing the understanding of multisensory integration. Although the process is under continuous development, there are several basic mechanisms of multisensory integration which have been explained and their effect towards a sensory target. Additionally, the world has come to a new era, witnessing a wide range of investigations into the field most of which exploit the physiological principles described above (Stein et al., 2009). A good number of these principles make use of information and evidence which has been borrowed and transferred from classical sensory applications; having acceptable fused information. From a wider perspective, it is noticeable that multisensory integration denotes existing differences between cross-modal reactions and responses elicited by single stimuli. However, more relevant research measures have to be incorporated in order to give a broader statistical approach.
Although there are outstanding issues surrounding physiological techniques, it is worth acknowledging the progress which has been realized through these developments in the understanding of multisensory integration (Stein &Stanford, 2008). A lot has been learned on some of the techniques and the behavioral impact of multisensory integration. This progress which has been realized in the field and the existing research indicates the desire to advance our understanding in neuronal multisensory integration.
References
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