Applications of Functional Magnetic Resonance Imaging for Brain Mapping Research Paper

Functional magnetic resonance imaging (fMRI) is a method that quantifies brain activity through the measurement of blood flow and amount of oxygen in the blood (Mohamed et al. 3). Extremely powerful radio waves change the atomic positions in the body and aid in obtaining images from the areas where these changes are taking place. These waves reflect a signal that is interpreted to reveal the tissue composition (the anatomy of the brain or the activity of the brain in the form of blood flow). MRI provides motionless pictures of anatomical organization of internal body parts such as the brain using computers (Alac & Hutchins 629). Brain mapping entails the identification of brain regions involved in responses to external stimuli (Varoquaux, Gramfort & Thirion 1). Brain mapping is actually carrying out a functional localizer, which is the concentration of tasks to specific regions of the brain (Friston et al. 8). In a brain MRI scanning session, hydrogen ions in the tissues of the brain release indicators that are recognized by a computer (Alac & Hutchins 631). These signals get into the computer in the form of numerical data that the computer changes into brain images. Therefore, fMRI images reveal the level of activity in different regions of the brain (Daimiwal, Sundhararajan, & Shriram 1). Images obtained while a subject is carrying out a given cognitive task can show the parts of the brain that are most active in that particular task. Using various colors on the images shows how the dissemination of activity in the brain varies with time (Alac & Hutchins 631). This technique is used in a variety of ways to establish maps of active processes in the brain such as lying or telling the truth (Alac & Hutchins 632).

Some lie detection techniques use non-verbal cues, for example, perspiration, facial expressions, respiration, and body movements to recognize dishonesty (Mohamed et al. 1). These methods have their disadvantages that necessitate the development of more advanced techniques such as the infrared thermal imaging and the standard polymorph. However, a polygraph also has its drawbacks. For example, it solely relies on quantifying responses of the sympathetic nervous system, a parameter that is not unique to lying and occurs during other emotional states such as exhilaration, remorse and annoyance (Mohamed et al. 2). This paper looks at the various applications of fMRI.

Applications of fMRI for Brain Mapping

Functional MRI is one of the techniques that spot regions of the brain associated with some motor and sensory tasks. Blood Oxygenation Level-Dependent contrast (BOLD) is the most prevalent fMRI technique that captures functional images of the brain. The neural brain activity due to motor or sensory tasks causes localized alterations in the flow of blood. Therefore, the resultant levels of oxygenation are subject to disparities (Daimiwal, Sundhararajan, & Shriram 1). Performance of tasks by areas of the brains increases the neuronal as well as the consumption of oxygen and glucose. Consequently, the hemodynamic and metabolic alterations that arise influence the oxygen content of the tissues that are easily detected by the MRI scanner (1). Brain mapping needs a speedy 2-dimensional imaging such as echo-planar imaging. The desired information is obtained from a series of images showing the oxygenation changes with time. Therefore, in fMRI a single experiment has several images recorded during various time intervals. Images obtained as the subject is carrying out a task (the ‘on’ state or activation state) are compared with images when the subject is not performing the task (‘off’ state or base line state) (Daimiwal, Sundhararajan, & Shriram 2). The variation between the strength of the images in the activation state and the baseline state gives the resultant signal. Activation maps, which show sections of the brain accountable for given tasks, are found from statistical tests of the means of the images.

Processing the signals obtained from fMRI involves several methods such as the “temporal spatial and spectral spatial representation” that makes use of frequency domain and time information (Daimiwal, Sundhararajan, & Shriram 3). The research gives a model by Friston et al. that describes a linear model for the hemodynamic response in fMRI time series (Daimiwal, Sundhararajan, and Shriram 3). The drawback of this model, however, is determining the hemodynamic response function that works together with the convolution of the stimulus function to give the activation signal (3). Worsley and Friston solve this problem by providing a statistical parametric mapping (SPM) that uses a generalized linear model operating at each voxel (Daimiwal, Sundhararajan, & Shriram 3). The linear model of the equation is “x=βG+e where ‘x’ is the unsmoothed time series and ‘e’ is the error vector whose components are independent and normally distributed with zero mean and variance 1” (Daimiwal, Sundhararajan, & Shriram 3). Using a Gaussian filter and GLM to sift and iron the data enables the fitting of the processed data into the voxel and the computation of the parameter β. The process then uses a t-statistic is to sense the considerably activated pixels (3).

Functional MRI has several clinical applications because it is a noninvasive technique that can be performed repeatedly. These applications include the assessment of the brain’s anatomy, checking the progress of brain tumors, guiding the planning of surgical treatments of the brain, and evaluating the consequences of stroke, trauma or degenerative illnesses on the functions of the brain (Daimiwal, Sundhararajan, & Shriram 4). In addition, fMRI helps establish the regions of the brain responsible for handling crucial functions such as speech, thought, movement, and feeling, a process known as brain mapping (Daimiwal, Sundhararajan, & Shriram 1).

The Use of fMRI in Brain Mapping of an Ecologically Valid Situation

The researchers in this study utilize BOLD contrast to reveal implicit rejoinders that are strongly linked to the action of the neurons (Mohamed et al. 1). This system facilitates the precise recording of brain sections that take part in superior cortical functions such as dishonesty and telling the truth (Mohamed et al. 2). A number of fMRI imaging studies reveal that activated sections of the brain during judgement and management of information are “the parietal lobes, prefrontal cortices, and anterior cingulated” (Mohamed et al. 3). The use of control question technique (CQT) and the widely accepted polymorph method reveals poor correlation between signals obtained from BOLD and the test scores of the polymorph. This study uses a tailored polygraph as a positive control and equates the findings to standard computerized polygraph dimensions using the Integrated Zone Comparison Technique (Mohamed et al. 4).

The researchers develop a working neurological mode of deception to guide their work. This model caters for data concentrating on the neural constituents of cheating, neural substrates associated with reward circuitry, and inhibition processes (Mohamed et al. 4). This model also depicts the sequences of proceedings involved in normal polygraph tests. The first step in giving a fib or an honest reply starts with hearing the question, comprehending it and then remembering an occurrence or a fact that connects to the question. Seeing or hearing the question stimulates the matching visual or auditory cortex. Receptive language comprehension links to initiation in Wernicke’s area, which comprises parts of “the superior temporal gyrus and the dominant angular cortex” (Mohamed et al. 5). The brain region that relates to feelings such as fear and anxiety is the amygdala, which is stimulated whenever an individual remembers events relating to anxiety. It is possible for the test subjects to recall events relating to anxiety and provide truthful responses. Therefore, the activation of the amygdala is not a deceiving or inhibition state of affairs, and a misinterpretation of this usually gives a wrong positive in the polygraph measurement (Mohamed et al. 5).

The subject strategizes a rejoinder that is in harmony with reality or falsehood after recollecting relevant occurrences. While planning a false response, an extra region of the brain is assembled to provide this response. A distinct activation of the same area can also produce a lie. Inhibition or hiding of the truth is the major facet of the construction that fMRI tries to uncover. Several studies come to the agreement that the prefrontal cortex area plans deceptive responses and covers up the truth. It is shown from fMRI studies that the anterior cingulate cortex and sections of the right hemisphere are triggered during lying, and that motor response is the final constituent of giving a true or false statement. The motor system situated in the frontal lobe gives this rejoinder.

This study explores the sections of brain instigation during lying and telling the truth using BOLD fMRI at 1.5 Tesla and a real-life situation (Mohamed et al. 6). It uses 11 subjects of an average age of 28.9 years. Random fMRI and polygraph tests are done using two situations. One scenario entails telling a lie about a gunshot incident (6 subjects), whereas the second scenario involves telling the truth about the same incident (5 subjects). Interviews and polygraph tests are carried out on all subjects, and the signals are recorded and analyzed. The first session, a lie only condition (LOC), establishes brain activity during lying and the second session (truth only condition-TOC) determines brain activity during truth telling. The obtained images are processed and analyzed then the two sessions are compared revealing that there are disparities between brain activation in lying and saying the truth (Mohamed et al. 11).

Polygraph scores reveal total correlation in the GS category (six subjects), whereas in the NGS (five subjects) category varying results are obtained giving accuracy of between 60 and 80 percent. Four out of the five subjects are correctly identified as truthful. Fourteen brain regions are found active during lying, whereas seven sections are identified as active when telling the truth.

The results of this study show that there are exclusive areas of brain function that can separate lying and telling the truth and that these two processes have distinct as well as overlapping regions.

Understanding fMRI Brain Images and Making Sense out Of Them

Carrying out scientific research entails many forms of cognitive processes such as classification, “reasoning, problem solving, and analogy formation” (Alac & Hutchins 629). The researchers tackle cognitive processes ensuing when scientists interrelate and show that these interactions are, in addition, cognitive processes. They direct their focus on the interpretation fMRI images to allow them comprehend the cognitive process of interpreting fMRI maps.

Alac and Hutchins combine participant observation with the microanalysis of given occurrences (632). The detailed microanalysis reveals the cognitive aspects of the observed practice (Alac & Hutchins 632). The ethnographic exploration involves recording the activities of various scientists in three laboratories. Fifteen subjects participate in the investigation for about nine months. Video recording, document analysis, direct observations, and semi-structured interviews are the data collection techniques that the study uses (Alac & Hutchins 632). A microanalysis on digital video recordings of scientific procedures reveals how scientists make meaning of complex fMRI images. These footages reveal synchronized demonstrations that help in interpreting the images.

The investigation of the visual brain areas involves six scientists in a laboratory. They realize that the overall orientation of visual sites across individuals is uniform and that the retinotopically planned visual areas are carbon copies of the retinal arrangement (Alac & Hutchins 634). In addition, they find out that the eye’s ocular characteristics propel stimuli, which are positioned next to visual zones in the adjoining retinal position. It is also seen that all visual information reaches the cortex of the brain through the primary visual area (VI) situated in the posterior occipital lobe of each hemisphere. The study analyzes five excerpts obtained from the interaction between an expert and a learner. The two participants sit before a computer with a brain image and discuss various sections of the brain. A phase map on the computer screen helps define early visual areas. The expanding ring stimulus reveals how visual stimuli trigger responses of the neurons. The expert makes a chart, which she uses as a collective architecture for seeing. The expert reveals that the chart is her own way of understanding retinotopic mapping. She further says that making the chart makes her understand verbal instructions and that she frequently uses the chart to teach other people. While explaining the retinotopic map and identifying its center, the expert points to the probable location of the fovea of the brain image even though she is not sure of the exact location (Alac & Hutchins 647). This implies that understanding an unknown concept entails transcribing the known to the unknown (647). The rotating wedge phase map helps to sketch boundaries amid the visual areas.

The study also finds out that linguistic expressions together with gestures are employed with the phase map and that language and gestures describe what does not exist in the brain. While explaining an unknown phenomenon, an individual can supplement the unknown information with dynamic and fictitious information. These elements are of utmost significance in the implementation of cognitive tasks.

Brain Mapping Psychological Processes Using Psychometric Scales

Linking brain activity to psychological processes is a significant aspect in social sciences. Previous studies involving fMRI use multiple stimuli to provoke activation in areas of the brain areas that are consistent to psychological processes, but the connection between psychosomatic practices and their equivalent neural correlates is vague (Dimoka 1). A clear connection enables social scientists to comprehend the “underlying brain functionality of psychological processes to advance their neurological understanding of these processes” (Dimoka 1). Such information is also valuable to neurologists in building detailed functional maps of the human brain.

The study conducts two fMRI tests to examine a proposed brain mapping technique with four psychological processes with “well-established self-reported psychometric scales” (Dimoka 2). The initial experiment involves trust and mistrust, whose neural correlates are known. The second study, on the other hand, uses two psychological processes with unknown neural correlates (perceived ease of use and perceived usefulness). The first experiment aims to certify the neural correlates of the published literature, whereas the second study seeks to test the method using parameters with unknown neural correlates. The first set uses 15 right-handed subjects and exposes them to a three Tesla Siemens fMRI scanner continuously. Statistical data analysis uses the general linear model in SPM5 to check the contrast based on BOLD. The second experiment utilizes a different set of 15 subjects and exposes them to fMRI scanning as they view two websites and compare their perceived usefulness and ease of use.

The study observes that the high trust seller in the first test stimulates significant activation in the caudate nucleus, putamen, and anterior paracingulate (Dimoka 4). The putamen and caudate nucleus are the brain’s ‘reward’ centers that are frequently associated with trust (Dimoka 4). The anterior paracingulate captures when an individual acts cooperatively and is associated with social inferences. The orbitofrontal cortex, an area that computes uncertainty is stimulated in distrust. The bilateral amygdala and bilateral insular cortex are also activated in distrust. All these values are consistent with those in the literature. In the second experiment, ease of website use stimulates the anterior cingulated cortex and caudate nucleus. Low usefulness, on the other hand, stimulates the activation of the insular cortex, which is associated with the fear of loss. These findings show that perceived usefulness relates to prospects of good results from using the technology, and this is why apparent usefulness corresponds to the reward area in the brain (Dimoka 5). Conversely, a badly planned technology is linked to a low degree of supposed usefulness. This is mapped onto the brain as a possibility of loss from using that technology.

The Use of fMRI in Detecting Decision-Making Impairment

The Iowa Gambling Task (IGT) is an extremely sensitive test for the recognition of decision-making impairment in a number of neurologic and psychiatric conditions (Li, Lu, D’Argembeau, Ng, & Bechara 410). Neurological patients often have brain damage in areas such as the mesial orbitofrontal and the bilateral amygdala. They often get poor IGT results. Damage to the parietal cortex also causes poor IGT performance. IGT performances categorize a number of psychopathological conditions such as pathological gambling, substance addiction, obsessive-compulsive disorder, schizophrenia, anorexia nervosa, chronic pain, attention deficit among many others (Li et al. 411).

The study uses right-handed participants with a mean age of 23.1 years to investigate brain activity during an IGT session. The original version of IGT decks (ABCD) is used together with three additional decks (KLMN, EFGH, and IJOP). The subjects are asked to choose a card from each of the decks as the computer program traces the sequence of the selected cards. Selecting a card is associated with a loss or gain that the computer screen displays every time the participant chooses a card. The subjects have at most four seconds to decide and failure to choose a card within the stipulated time results in an automatic, random selection of a card by the computer. The subjects use four buttons of a fMRI-compatible box instead of the computer mouse to select the decks (Li et al. 414). The study uses a regression analysis to test the obtained data for reward and risk processing and errors in prediction.

The net score of each block of cards is determined by getting the difference between the total advantageous decks and the total disadvantageous decks. Consequently, subjects with scores below zero are considered to make disadvantageous selections, whereas those with scores above zero are seen to make advantageous selections. These scores enable the categorization of the participants into learners (scores below zero) and non-learners (scores above zero). The researchers hypothesize that the possible reason for the low scores in the learners is that they have immature prefrontal cortex. The fMRI results from the three decks give similar results of the brain-activated regions showing that it is possible to localize activation using one version of the IGT (Li et al. 417).

Conclusion

The use of fMRI in brain mapping plays a significant role in various disciplines such as the medical field, psychological field, education field, and law enforcement (truth and lie detection). Different experiments by various researchers reveal that similar areas of the brain are responsible for performing particular tasks. Therefore, this paper concludes that fMRI is a reliable tool in determining the regions of the brain that are responsible for cognitive tasks.

Works Cited

Alac, Morana and Edwin Hutchins. “I See What You Are Saying: Action as Cognition in fMRI Brain Mapping Practice.” Journal of Cognition and Culture. 4.3 (2004): 629-661. Print.

Daimiwal, Nivedita, Sundhararajan M., and Revati Shriram. “Applications of fMRI for Brain Mapping.” International Journal of Computer Science and Information Security, 10.11(2012): 1-5. Print.

Dimoka, Angelika. “Brain Mapping of Psychological Processes with Psychometric Scales: An fMRI Method for Social Neuroscience.” NeuroImage (2010).

Friston, J. Karl, Pia Rotshtein, Joy J. Geng, Philipp Sterzer, and Rik N. Henson. “A Critique of Functional Localizers.” Foundational Issues in Human Brain Mapping. Eds. Stephen Jose´ Hanson and Martin Bunzl. Massachusetts: The MIT Press, 2010. 3-24. Print.

Li, Xiangrui, Lu Zhong-Lin, Arnaud D’Argembeau, Marie Ng, and Antoine Bechara. “The Iowa Gambling Task in fMRI Images.” Human Brain Mapping. 31.2010 (2010):410-423. Print.

Mohamed, B. Feroze, Faro H. Scott, Nathan J. Gordon, Steven M. Platek, Harris Ahmad and Williams, J. Michael n.d., Brain Mapping of Deception and Truth Telling about an Ecologically Valid Situation: An fMRI and Polygraph Investigation. Web.