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Neural oscillations are at the core of important computations in the mammalian brain. Interactions between oscillatory activities in different frequency bands, such as delta (1–4 Hz), theta (4–8 Hz) or gamma (>30 Hz), are a powerful mechanism for binding fundamentally distinct spatiotemporal scales of neural processing. Phase-amplitude coupling (PAC) is one such plausible and well-described interaction, but much is yet to be uncovered regarding how PAC dynamics contribute to sensory representations. In particular, although PAC appears to have a major role in audition, the characteristics of coupling profiles in sensory and integration (i.e. frontal) cortical areas remain obscure. Here, we address this question by studying PAC dynamics in the frontal-auditory field (FAF; an auditory area in the bat frontal cortex) and the auditory cortex (AC) of the bat Carollia perspicillata. By means of simultaneous electrophysiological recordings in frontal and auditory cortices examining local-field potentials (LFPs), we show that the amplitude of gamma-band activity couples with the phase of low-frequency LFPs in both structures. Our results demonstrate that the coupling in FAF occurs most prominently in delta/high-gamma frequencies (1-4/75-100 Hz), whereas in the AC the coupling is strongest in the delta-theta/low-gamma (2-8/25-55 Hz) range. We argue that distinct PAC profiles may represent different mechanisms for neuronal processing in frontal and auditory cortices, and might complement oscillatory interactions for sensory processing in the frontal-auditory cortex network.
Humans and other primates are highly visual animals. Our daily visual activities such as recognizing familiar faces, interacting with objects, or reading, are supported by an extensive system of interacting brain areas. The interactions between the many individual nerve cells both within and between brain areas need to be coordinated. One possible solution to achieve flexible coordination between cells in the network is rhythmic activity, or oscillations. The focus of the thesis will be activity in the largest visual area, V1, in non-human primates. In V1, high-frequency activity, so-called gamma-band activity (“gamma”, ca. 30-90 Hz) can be frequently observed and has been suggested to play a role in coordinating activity in the visual system. In Chapter 1, the coordination problem, the primate visual system and gamma-band oscillations are introduced in detail. The following chapters explore the dependence of gamma on contextual influences. Does V1 use contextual information to optimize co-ordination? In the first part, the short-term consequences of repeated encounters with visual stimuli on V1 responses are explored (Chapters 2 and 3). Inspired by results from colored, naturalistic images in the first part, the second part tests the dependence of gamma on spatial and chromatic stimulus aspects (Chapters 4 and 5).
Stimulus repetition is a simple yet powerful way to tap into our brains’ ability to learn and adapt to our environment. Repeated presentation of a visual stimulus tends to decrease responses to this stimulus. Is this accompanied by changes in the coordination of brain activity? In Chapter 2, the stimulus-specificity of repetition effects on gamma was tested using naturalistic stimuli. V1 is most typically studied using black-and-white, artificial stimuli that are very familiar to the animals. Here, colored natural images were repeatedly presented that were initially novel to the animals, to provide a wider and more naturalistic range of stimulation. Both multi-unit spiking activity (MUA) and gamma showed stimulus-specific repetition effects. MUA responses de-creased most strongly for initial repetitions and less for later repetitions. In contrast, gamma could increase or decrease for initial repetitions, but tended to increase for later repetitions. This points to the operation of multiple plasticity mechanisms. One process may rapidly decrease MUA and gamma and be related to initial novelty or adaptation. The other increases gamma, is active for more repetitions, and could constitute a form of refinement of coordination over time. Moreover, based on the spacing of stimulus repetitions, stimulus memory in V1 persisted for tens of seconds.
In the following Chapter 3, the stimulus location specificity and persistence of the repetition effects for longer timescales were tested. To this end, the observation that the increase in gamma with repetition was strongest for the first tens of repetitions was used to test for location specificity and memory. Using simple artificial stimuli that were repeated many times at two alternating locations, both location specificity and memory on the order of minutes was observed. Due to the structure of the primate visual system, location specificity suggests that the repetition effects involve early to mid-level visual areas such as V1. Memory for previous stimulus presentations on the order of minutes has not been previously reported for V1 gamma. Taken together, these experiments demonstrate short-term plasticity of gamma that is stimulus- and location specific and persists on the timescale of minutes.
In Chapter 2, the average gamma-band response to the large, naturalistic stimuli was highly stimulus dependent. Relative increases in gamma-band activity scaled between tens and thousands of percent change depending on the stimulus. Particularly the color of the stimuli appeared to play a strong role, although the stimulus set was too limited and uncontrolled to draw strong conclusions. In Chapters 4 and 5, underlying mechanisms for the stimulus specificity of gamma were explored using more well-controlled, artificial stimuli that varied in color and spatial structure.
Much of vision relies on the analysis of spatial structure. Each nerve cell in V1 only responds to visual stimuli in a particular, small part of the visual field, its so-called “receptive field” (RF). Compared to isolated RF stimulation, nearby cells that are stimulated by a similar structure from different parts of visual space can show response decreases, commonly known as “surround suppression”, and may show coordinated activity in the gamma band. In Chapter 3, responses to large, uniformly colored disks are contrasted with responses to black or white (achromatic) disks. A first experiment showed that gamma-band responses were stronger for colored than achromatic stimuli, whereas MUA responses could decrease below baseline for colored stimuli. To test whether these phenomena were related to surround suppression, stimulus size was manipulated in a second experiment. When stimuli were of sufficient size to induce surround suppression, clear gamma-band responses emerged. Surround suppression and gamma were stronger for chromatic stimuli. However, the change of stimulus size could have changed not only surround suppression but also stimulus saliency. Therefore, in a third experiment, the overall size of the stimulus was kept constant, and the spatial structure of the stimulus was manipulated. In comparison to uniform, predictable stimulus structure, mismatches between the center of the stimulus and the surrounding visual space led to strong increases in MUA responses and strong de-creases in gamma-band activity. These effects were restricted to the recording sites with RFs at the mismatch location. These experiments underpin the strong role of both spatial structure and color for gamma in V1.
In Chapter 4, responses to different color hues are studied in more detail. Gamma response strength depended on hue, being strongest for red compared to blue and green stimuli when measured with a gray background. To better understand the underlying mechanisms of the differential responses, the spatio-temporal context in the form of the background color was manipulated. Background color had a strong influence on gamma strength. Using differently colored backgrounds, different parts of the color signaling pathways could be adapted. Response differences to different color hues could be explained well with a model that incorporates differences in adaptation between pathways involving long- compared to medium-wavelength cone signals.
Taken together, these experiments indicate a strong role of both spatial context (stimulus size and structure) and temporal context and drive (repetition, adaptation) for the generation of gamma-band activity in V1. Functional implications of these dependencies are considered in the final Chapter 6, and a role for gamma-band syn-chronization in a coding regime for visual inputs that generate strong drive and high predictability is suggested.
Use-dependent long-term changes of neuronal response properties must be gated to prevent irrelevant activity from inducing inappropriate modifications. Here we test the hypothesis that local network dynamics contribute to such gating. As synaptic modifications depend on temporal contiguity between presynaptic and postsynaptic activity, we examined the effect of synchronized gamma (ɣ) oscillations on stimulation-dependent modifications of orientation selectivity in adult cat visual cortex. Changes of orientation maps were induced by pairing visual stimulation with electrical activation of the mesencephalic reticular formation. Changes in orientation selectivity were assessed with optical recording of intrinsic signals and multiunit recordings. When conditioning stimuli were associated with strong ɣ-oscillations, orientation domains matching the orientation of the conditioning grating stimulus became more responsive and expanded, because neurons with preferences differing by less than 30° from the orientation of the conditioning grating shifted their orientation preference toward the conditioned orientation. When conditioning stimuli induced no or only weak ɣ-oscillations, responsiveness of neurons driven by the conditioning stimulus decreased. These differential effects depended on the power of oscillations in the low ɣ-band (20 Hz to 48 Hz) and not on differences in discharge rate of cortical neurons, because there was no correlation between the discharge rates during conditioning and the occurrence of changes in orientation preference. Thus, occurrence and polarity of use-dependent long-term changes of cortical response properties appear to depend on the occurrence of ɣ-oscillations during induction and hence on the degree of temporal coherence of the change-inducing network activity.
Surface color and predictability determine contextual modulation of V1 firing and gamma oscillations
(2019)
The integration of direct bottom-up inputs with contextual information is a core feature of neocortical circuits. In area V1, neurons may reduce their firing rates when their receptive field input can be predicted by spatial context. Gamma-synchronized (30–80 Hz) firing may provide a complementary signal to rates, reflecting stronger synchronization between neuronal populations receiving mutually predictable inputs. We show that large uniform surfaces, which have high spatial predictability, strongly suppressed firing yet induced prominent gamma synchronization in macaque V1, particularly when they were colored. Yet, chromatic mismatches between center and surround, breaking predictability, strongly reduced gamma synchronization while increasing firing rates. Differences between responses to different colors, including strong gamma-responses to red, arose from stimulus adaptation to a full-screen background, suggesting prominent differences in adaptation between M- and L-cone signaling pathways. Thus, synchrony signaled whether RF inputs were predicted from spatial context, while firing rates increased when stimuli were unpredicted from context.