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Booksummary: Principles of Cognitive Neuroscience
Te gebruiken bij
Auteur(s): Purves, D., Cabeza, R. Huettel, S.A., LaBar, K.S., Platt, M.L. and Woldorff, M.
Druk/Jaar van uitgave: 2013
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The goal of cognitive neuroscience is to use the function of the brain and the nervous system to explain cognition and behaviour. Cognitive psychology pointed out the importance of measurement during cognitive and perceptual tasks to investigate neural activity is converted to action, thought and behaviour. Neuroscience has two categories (Figure 2.1 on page 19). The first is researching changes in cognitive behaviour when the brain has been stimulated, for example by trauma, medication or electronic stimulation. The other category is measuring brain activity when carrying out tasks using electrophysiological and imaging techniques.
Brain Imaging Techniques
X-ray techniques have been used for a long time to make non-invasive images of the human body. Contrast agents can be injected to enhance the contrast of the picture. The first technological use of this was computerized tomography (CT) (Figure A on page 22). A CT uses X-rays to gather intensity information from multiple angles. The data can be viewed in ‘slices of tissue’, called tomograms.
Magnetic Resonance Imaging (MRI, figure B on page 23) is faster and cheaper than CT. MRI uses strong magnets to ‘feed’ energy to protons in the water of the cell tissue, which move in the frequency of radio-wavelength. When the magnet is turned off, the protons in the body release the energy. The scanner measures excitation of energy by the protons. The proton density differs in every tissue, which enables the computer to calculate a clear image of different tissues. The spatial resolution of MRI is about one millimetre. MRI is non-invasive, has a high spatial resolution and can be made sensitive to different kinds of tissues.
Structural Imaging Techniques
Researchers use different methods to investigate the connections between brain areas. A variant of MRI, diffusion-weighted imaging, can allocate the white matter fibre tracts in the brain. It shows the local diffusion of water. Diffusion tensor imaging (DTI) quantifies the diffusivity of water molecules. Most axonal fibre tracts in the brain are encased in hydrophobic myelin, which makes water more diffused along the tracts.
White matter shows a preferred direction of diffusion (anisotropy), whereas other regions have no preference (isotropic). The amount to which a voxel (imaged pixel of MRI) is anisotropic is called the fractional anisotropy. Fractional anisotropy gives information about the tissue within a voxel. Voxels with fractional anisotropy in the same direction can be connected to each other to ‘draw’ a fibre tract in a MRI image (Figure B on page 24). DTI can be combined with fMRI. Researchers are trying to reconstruct the whole network of connections in the brain (the connectome). This research is called connectomics, but it is expensive and the outcome is unclear. At microscopic level, a method called Brainbow is used to contrast individual neurons and their connections. An electron microscope can also make photographs of single neurons.
Brain disturbances explaining cognition
Making clinical-pathological correlations is the oldest method investigate the connection between the brain, thoughts and behaviour. When a brain area and a cognitive function are both disrupted, it is likely these two are connected. First, the connection could only be discovered by autopsy. Due to modern techniques we can now research this connection in living patients. A major restriction of clinical-pathological correlations is that brain damage can have many causes that are not under the control of the researcher. Also, brains differ from person to person, which makes it hard to generalise the results. Researchers can use imaging techniques to make an image of patients with similar symptoms. Then they layer the affected areas on top of each other: the regions that overlap are likely to be the cause of the symptoms.
Researchers can also deliberately make lesions in the brain of non-human subjects to get a more direct cause-effect picture. However, lesion studies in humans and animals have interpretation problems. Damaged connections in the brain do not longer transmit information to other areas and can cause problems as well. The symptoms can be mistakenly attributed to the damaged area, instead of the area with the missing input. This interpretation problem is known as diaschisis.
Pharmacological products can disrupt neurotransmitters in the nervous system. Researchers have two methods to find out how medicines affect the brain. The researcher can obtain cognitive data from people with a long history of drug use. An example is the operation of the dopamine system (the reward system) of drug addicts.
Another more controlled method is administering drugs and observing their effects in an experimental setting. Substances that activate neurotransmitter receptors are called agonists; substances that block the receptors are called antagonists. A disadvantage of this method is the uncertainty about the effects of drugs on specific areas. The whole brain is affected. A solution can be to inject the substances straight into specific brain regions.
Intracranial stimulation is direct electronic brain stimulation. This invasive method uses electrodes placed on specific brain areas. Temporarily of chronically placed electrodes stimulate the area during cognitive tasks. Specific information about the function of the area can be obtained by varying the amount of stimulation. Moderate stimulation enhances or elicits behaviour, whereas strong stimulation disrupts behaviour (like lesions). This method is used by brain surgeons to map important areas that have to be avoided during surgery.
There are several types of extracranial brain stimulation. During Transcranial Magnetic Stimulation (TMS) an experimenter gives a powerful magnetic pulse on the scalp of a subject (Figure 2.3). The induced magnetic-electrical field can stimulate or disrupt processes, depending on the intensity of the pulse. The technique is almost like direct electric stimulation, except that the effects are temporal, reversible and less invasive. During repetitive TMS (rTMS), repetitive pulses are administered for a longer period of time. The cognitive and behavioural effects are measured afterwards.
Another method is to measure the influence of the timing of the pulses at different intervals during a task trial. It provides a better temporal resolution of the influence of a brain region on a cognitive task. TMS has several disadvantages. It has a low spatial resolution, because TMS disturbs a large area of the brain during the pulse. The stimulation doesn’t penetrate very deep into the brain either: only about 1,5 centimetres. TMS mainly affects the cerebral cortex. TMS can also induce twitching: the field also affects the muscles in the head. Lastly, not everyone is suited for TMS. It can induce epileptic seizures.
Extracranial stimulation can also be administered by transcranial direct current stimulation (tDCS). It is a continuous, low-amplitude, electrical current placed on the scalp. An electrode is placed on the area of interest. There are two types of stimulation: anodal (enhancing cortical excitability) and cathodal (decreasing cortical excibility). Subjects either have real stimulation or a placebo. The effects of tDCS last for a period of time after the session (just like rTMS). The method is simple, cheap and has several scientific and clinical implications. tDCS also has drawbacks: it has low spatial resolution and provides only limited understanding of its workings.
Optogenetics has high neuronal discrimination and a high temporal resolution. It uses genetics and laser light to activate neural systems or cells types.
Ion channels in neurons open or close when the current of an action potential passes by. Optogenetics alters neurons in such a way that they excite or inhibit after stimulation by a specific wavelength of light. The genes to make neurons sensitive to light are extracted from algae and implanted in a carrier virus, which gets injected to the brain area.
Measuring neural activity
There are several methods to measure brain activity while cognitive tasks are performed. One method is direct electrophysiological recording. The most popular version of this is single-neuron electrical recording of the action potentials. During extracellular recording, electrodes are placed into the space around the neurons, measuring the neural activity of one or multiple cells. For intracellular recording, a fine glass electrode is inserted in one single neuron.
Often, the record device can be moved in different directions in the animal’s brain. Researchers often use two different methods to obtain single-unit data. A peristimulus time histogram (PSTH, figure 2.5B on page 30) shows the activity of a neuron per trial and time-locked. Another method is using neuronal tuning curves. Stimuli are varied in a specific dimension (colour, orientation). Then the strength of the neural response is measured and plotted.
The resulting curve shows the sensitivity of the cell to the different dimensions. Multielectrode recording arrays involve patches with multiple electrodes to measure a whole field of neurons. Direct electrophysiological recording is only done to animals. However, it takes much effort to set up the research. This approach can’t measure complex human cognition.
Electroencephalographic recording (EEG) is a non-invasive method to measure electrical brain waves on the scalp. It uses electrodes filled with a conductive substance to pick up voltage fluctuations. The computer compares the voltage differences between each separate electrode and a reference electrode. EEG measures dendritic field potentials (Figure 2.7 on page 33) of clutches of neurons. Dendrites are often oriented vertically to the surface of the cortex.
The action potential causes a current flow along the dendrites. The electrodes of the EEG-cap pick up this temporal change in voltage. Dendrite field fluctuations are called local field potentials (LFPs) when they are measured inside the scalp. They show the integrative processing of large cortical neurons. EEG signals are separated in different frequency bands:
Delta, <4 Hz
Theta, 4-8 Hz
Alpha, 8-12 Hz
Beta, 12-25 Hz
Gamma, 25-70 Hz
High gamma, 70-150 Hz
The relative power in these bands represents the general state of the brain, such as arousal. Event-related potentials (ERPs, Figure 2.8 on page 34) are calculated using multiple time-locked pieces of the ongoing EEG. They show the neural activity of processing with a high temporal resolution. The peaks in an ERP are named according to their electrical polarity and latency, or according to their order in the image.
Although the temporal resolution of ERPs is relatively high, its relative poor spatial resolution makes it difficult to find out the exact source of activity. However, it is not impossible to map relative amounts of activity at different places on the scalp. The inverse problem makes it difficult to find out the exact clutch of neurons in the brain causing the activity: it could be any set. Besides time-locked averaged ERPs, researchers can also use oscillatory activity in the different bands of the EEG signal to investigate cognitive functions.
Magnetoencephalography (MEG, figure 2.10 on page 37) uses magnets to record event-related magnetic-field responses (ERFs) from ongoing MEG signals. It is similar to EEG, but it uses the magnetic field of the brain instead of the electrical fluctuations on the scalp. Using the ‘right-hand rule’ from physics, we can find the flow of a magnetic field around a current. MEG measures the magnetic fields and calculates the flow of the action potentials in dendrites.
MEG and EEG also differ in physical properties: MEG is relatively insensitive to activity in gyri. However, magnetic fields in the sulci are ‘sticking out’ of the head which makes MEG sensitive to activity in the sulci. EEG picks up activity in both sulci and gyri. MEG has a better spatial resolution, because EEG currents can have distortions due to the variable resistances of the head. MEG does not have this problem. Also, MEG picks up simpler signal distributions from the sulci.
Positron emission tomography (PET) measures changes in blood flow and metabolism of oxygen by the brain. Unstable positron-emitting isotopes are synthesised in a large tube. The isotope mostly used in PET is oxygen-15 in water molecules, which has a short half-life. When a particular brain area needs extra oxygen, which is a sign of extra activity, these molecules are distributes to that area in a few seconds. When the instable isotope decays, it may collide with an electron. This collision results in gamma-rays in opposite directions. Detectors in the tube only report registered rays when they appear in opposite direction. The computer then calculates the exact position of the collision. Due to this analysis, the temporal resolution is lower than expected. It also takes a lot of time to get a good signal. Experiments using PET use a blocked design in which several blocks of sessions come after each other.
Haemoglobin is a substance found in red blood cells, which can bind oxygen. Oxyheamoglobin carries an oxygen molecule and deoxyheamoglobin carries none. They have different magnetic resonance (MR) signals. The concentration of oxyheamoglobin indicates activity in the brain. Changes in concentration cause changes in magnetic resonance. This is known as the blood oxygenation level-dependent (BOLD) response, which is used to make fMRI images. fMRI has a better spatial resolution and a much better temporal resolution than PET. It does not require a radioactive injection, which makes fMRI non-invasive. fMRI is often used in an event-related design, in which trials take up only a few seconds (Figure 2.13 on page 41 for a comparison fMRI and PET). The trial blocks can have multiple stimuli which enables researchers to connect behavioural responses to neural responses.
The analysis of fMRI data can be done in different ways. Although information about local differences in MR can give interesting information about the function of certain brain areas, it is barely used in fMRI analysis. Researchers often apply spatial smoothing on the fMRI data to improve sensitivity to the stimuli. To find patterns in the data, researchers use pattern classification algorithms. The most common analysis is the multivoxel pattern analysis (MVPA), which searches for stimulus- or event-related patterns of activation across voxels. Total increase or decrease of activation in a certain brain area is less important. Repetition suppression is the tendency of the brain to supress a response to stimuli that look similar to the previous presented stimulus. When this principle is used in fMRI it is called fMRI adaption. The idea is that when repetition suppression occurs to a certain stimulus-pair, these stimuli share the same process in a brain area.
Information between brain regions is transported through fibre tracts. We know that some areas are better connected than others, but we do not know much about the functional connectivity. Using functional MRI, this question can be investigated. The simplest relationship between brain areas is co-activation: two or more brain areas adapt similarly in reaction to an experimental condition. To show this, researchers investigate the resting-state connectivity. Brain regions in resting subjects always show some random activation. Brain areas with co-varying fluctuations are believed to be connected.
Researchers use algorithms to search for simultaneous activation in the data. A seed voxel is a reference voxel: the signal fluctuations in this this particular voxel is compared to other regions. Brain regions that show resting-state connectivity tend to show functional connectivity during tasks as well. However, when a connection is found, the relationship between the two areas remains unclear. Combining fMRI and behavioural data (psychophysiological interaction, PPI) can help. A large disadvantage of fMRI and many other neural activity based methods is that they cannot confirm a causal relationship between brain areas. Methods such as structural equation modelling predict the best causal model based on the obtained data. A related approach is dynamic causal modelling, which makes models of the functional connections between brain areas and predicts how the connections change as a result of experimental manipulations.
Active brain tissue transmits and/or reflects light in a different manner than inactive brain tissue. These differences can be recorded and result in optical brain imaging. The method can be based on hemodynamic changes in response to neural activity, just like fMRI. However, the scalp has to be opened and illuminated with red light with a wavelength between 500 and 700 nanometres.
Another method is event-related optical signals (EROS) is a non-invasive activity-dependent mechanism. It also uses light, but can be applied outside the skull. It has high temporal resolution, but low spatial resolution. It does not come with the inverse problem.
Assembling and delineating
Neuroscience and cognition can be combined by connecting certain brain areas to cognitive functions. This association can be investigated using a double dissociation (Figure 2.16 on page 47). If Task A is mainly associated with Neural System A, and Task B associated with Neural System B, there would be patients with a particular brain lesion which impairs Task A, but not Task B. Subsequently, if a patient has a lesion in Neural System B, Task B would be impared as well, but not Task A.
However, neural systems often turn out to be only a bit independent. Task A and B can both be impaired to some degree at the same time. The double dissociation technique can also be used in brain activity studies. If Brain Area A is activated during Task A, we can say that there is an association. However, as with the lesion method, Task A and Task B can both be impaired to some extend even when the same brain area is activated.
Table 2.1 on page 48-49 provides an overview of all techniques and main advantages and disadvantages.
The limitations of each method, as well as their complementary scales, stimulated the use of a combination of the measurement techniques. Information obtained through a combination of techniques can be used across studies to synthesize findings relevant to particular functions. Information can also be directly combined across methodologies within the same or linked studies. However, combining data from different methods can be difficult to put in practice.
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