The study of human consciousness and perception has traditionally been ignored amongst the hard sciences due to its subjective and therefore assumed un-measurable nature. Studying the subjective aspects of the human condition has traditionally been left to the softer sciences of psychology and sociology and even considered to be more in the realm of philosophy and religion. However, recent applications of quantum physics, chaos theory, neurosciences, and even plasma, fluid, and solid state dynamics have opened the door to studying the subjective aspects of the mind and what have been termed the “neural correlates of consciousness”. Proposals for a theory of consciousness have ranged from quantum approaches applied to microtubules (Orch-OR Theory; Penrose and Hammeroff) and ion channels (Bernroider) to electromagnetic theories (Vitiello, Frohlich) and even the application of chaos theory to algorithms produced in the brain (Vandervert). Most proposals have subsequently been disproven by empirical data showing that the thermal temperatures present in the brain could not harbor the quantum effects suggested coupled with their inability to explain how the human mind combines a wide-range of stimuli into coherent experiences (the binding problem). Just as well, “mind as computer” theories are harshly debated in the scientific community with little scientific evidence correlating said theories with the exquisite nature of neural functioning. However, recent studies in gamma frequency oscillations and their corresponding neural correlations seem to be filling in the blanks that have traditionally made studying consciousness and perception so difficult. This blog will discuss the findings of these studies, the bio-physical correlates and the effects of gamma oscillations on coherency and perception within the brain.
In the last two decades advances in neuroscience and the use of electroencephalography (EEG), and magnetoencephalographic (MEG) techniques have solidified the observation that brain regions communicate by synchronizing the firing of neurons. The rhythmic input that is produced in the extracellular field potential results in brain oscillations represented by delta (0–4 Hz), theta (4–8 Hz), alpha (8–12 Hz), beta (12–30, Hz) and gamma (30–200 Hz) frequencies respectively. Previously thought to be a bi-product of waking, sleeping, and dreaming states, research in the past two decades has uncovered the possibility of these frequencies (especially those in the gamma range) representing a more causal roles in normal cognitive processes including memory, attention, perceptual binding and the experience of consciousness. Experimental data shows that gamma oscillations become highly correlated during different perceptual tasks amongst long-range neural networks which may lead to the creation of a unified field of perception.
Initial experimentation by Singer and Grey (1989) analyzing the visual cortex of cats presented with moving bars of varying orientations produced results showing that gamma oscillations work to synchronize inter-columnar input in the cortex when the bars were perceived. During a cycle of gamma frequency oscillations the neurons in different parts of the cortex fired “in phase” (i.e at the same time) leading to the proposition that gamma oscillations helped to “bind” different aspects of the scenery and convey a unified representation (Williams 2010). Further studies have found that the firing of cells in the visual cortex and elsewhere can become highly correlated over distances of many millimeters during perceptual tasks (Robinson 2007). Most studies of cortical network dynamics have focused on “random wiring” or “neighborhood couplings” however, recent studies point to more complex state of activity by utilizing local and long-range “patchy connections” (horizontal connections). Patchy projections seem to provide an exceptionally efficient way of wiring, as the resulting networks use significantly reduced wiring costs. Furthermore,” the eigenvalue spectra, as well as the structure of common in and output of the networks suggest that different spatial connectivity patterns support distinct types of activity propagation” (Voges 2009). In particular, the existence of strong two-point correlations in inter-columnar processing was closely associated with the oscillatory behavior in the gamma range. Two-point correlations of firing rates or local field potentials often show peak near-zero-time lag, even amongst easily detectable axonal conduction delays between the cells of interest. Correlations between cells are found to be highest when subjects are called upon to use similar preference features (line orientation, ocular dominance, etc.) and lessened as the disparity of presented stimuli increased (Robinson 2007). In cases where multiple stimuli were presented simultaneously, neural-cells partitioned off in “highly correlated groups each of which corresponded to one stimulus with little correlation between groups” (Robinson 2007). In comparison, the arousal of the same cells when presented with only one stimulus resulted in activity amongst all cells. Although changes in gamma activity were found to be statistically insignificant when a stimulus was perceived and not perceived, the level of correlation of gamma activity increased dramatically between cells depending upon the type of stimulus perceived (i.e multiple or singular). Mean-field theory, normally applied to fluid, static, and plasma physics presents working formulae which show how mm-scale patchy connections can support the properties of gamma oscillations with the proper frequencies needed for spatial structure even when motivated by uncorrelated points. These occur via resonances associated with the periodic modulation of the network connections rather than being due to single-cell properties.
Building on the initial experiments of Singer and Grey, experiments by Bartos et al (2007) found that cortical and thalamic regions display accelerated sub-threshold gamma oscillations of neuronal membranes. Synchronization of these rhythmic movements were shown to be facilitated by intra-laminar neurons which fire rhythmic spike bursts in the gamma frequency range and exhibited wide-spread cortical projections. Experiments focusing on the hippocampus of mice in the temporal lobe showed that gamma oscillations arise from the precise interplay of the action potential ﬁring of excitatory glutamatergic pyramidal neurons and inhibitory GABAergic inter-neurons. Consequently, alternating pairs of current sinks and sources occur in the tissue, which require enhanced Na+/K+- ATPase activity to restore ionic gradients and to maintain excitability. ATPases enzymes are responsible for catalyzing the decomposition of adenosine trihosphate (ATP) in the andesonine diphosphate (ADP) and a free phosphate ion. Dephosphorylation reactions are responsible for the release of energy which is used to drive other chemical reactions. The local ATP consumption in neurons is rapidly counterbalanced by mitochondria via oxidative phosphorylation, mainly in response to changes in substrates and intracellular Ca2 +. The process requires sufficient glucose and O2 supply as well as proper activities of mitochondrial enzymes.
Results obtained by experimentation of gamma wave frequency oscillations and perception emphasize that neural synchrony does not require temporally synchronous inputs, but can be instead draw from a variety of seemingly non-related stimuli. Activated patchy connections in turn help to compose seemingly unrelated events and perceived objects into a coherent perception. It is also apparent that the fundamental cause for gamma oscillation synchrony is governed by the network eigenmode rather than single cell properties (although mean cellular characteristics determine wave properties) and correspond to biological functions in the brain such as ion gradients and enzyme catalyzation. Further exploration of these topics may lead to greater discoveries in brain functioning, neuro-degenerative diseases, and how the neural correlates of consciousness may function. They also show that consciousness and perception both have the ability to be studied empirically and that resulting data is significant in understanding the functioning of the brain, deepening bio-physical concepts, and understanding how humans process information.
Nosce te Ipsum,