Measurements of neuronal activity in response to sensory stimulation have always shown that the evoked response pattern, be it at single cell level or across neuronal populations, can be very variable. The observed variabilities in individual data sets have been considered to be signal noise, which can be removed by averaging under the assuption of a linear superposition principle between random background noise and a repetitive, stereotyped pattern of the evoked signal. This view has been challenged in recent years. The improvement of optical and electrophysiological data aquisition techniques and simultaneous recordings of neural networks in real time with high spatial and temporal resolution, as well as new methods of data analysis, made it possible to analyze on level of single trial recordings. It was shown that the observed variability is not necessarily of random origin, but reflects real conditions of highly dynamic cortical activity. According to latest views in neuroscience, this variability is associated with spontaneous neuronal activity. The variability within spontaneous activity, in turn, reflects different stages of the brain's perception, attention, and information processing. This led to the assumption that the brain generates an internal expectation based on individual experiences, which in turn can have a modulatory effect on the neuronal response behavior to a stimulus. Interareal mechanisms originating in thalamus, higher cortical areas or local neuronal spontaneous activity are discussed as different modulators with presumably different spontaneous dynamics. So far, it has been shown that spontaneous activity plays a major role in the temporal development of functional neural networks and in the processing of internal and external signals. This not only affects individual areas but also includes interareal interactions in various hierarchically organized pathways of information processing. From this knowledge, the central questions of systemic neurophysiology developed, namely how the brain encodes information in these dynamic networks and what influence modulatory mechanisms exert on information processing.
In the present work, the spatial-temporal dynamics of the spontaneous activity as well as the variability of the response behavior to external stimulation of the visual system of anesthetized cats in the context of interareal communication were analyzed. In Area 18, the spatial activity of large neuron populations was recorded using the optical recording method of Voltage Sensitive Dye Imaging (VSDI). Despite constant experimental and stimulation conditions, a high degree of variability in the neuronal responses to a repeated stimulus was also present in this study, which successfully could be linked to neuronal processes. In order to analyse the data variability, it was necessary to work with single trial recordings. VSDI data presented a special challenge due to their signal-to-noise ratio. Hence Identification and reduction of technical, physical and biological artefacts in the temporal structure of signals was of particular importance. Despite optimal recording conditions and removal of sources of interference, a remaining variability in the evoked recordings was found. Before stimulation, high and low phases of spontaneous activity could be identified on the basis of the VSDI recordings, in which activity patterns occurred which spatially resembled spatio-temporal activity patterns evoked by visual stimuli. The degree of excitation of the stimulated neural networks in area 18 could be proven to dependent on previous spontaneous states. Simultaneous electrophysiological recordings of action and field potentials activity and optical VSDI recording in area 18 as well as in hierarchically higher posterior suprasylvanic cortex (PMLS) were derived to investigate the role of interareal communication channels in this context.
In summary, it could be shown that the variations within the optical data are not based on biological or technical interference, but of neuronal origin and can represent an internal state due to their spontaneously occurring activity patterns. The extent of the spontaneous activity shortly before the stimulation influences the amplitude of the evoked activity. This relationship was also related to the topology of area 18 and showed a high degree of spatio-temporal dynamics. In addition, communication with the hierarchically higher visual area PMLS was analyzed and these activity patterns could be associated with the spontaneous states in area 18 and, thus, be classified as a feedback system. Overall, it can be stated that in the present study and with the analytical techniques established in the context of this work, clear indications could be found that suggest that internal states in the central nervous system play an essential role in the processing of sensory information. | English |