Steffen Katzner

Local Origin of Field Potentials in Visual Cortex

The local field potential (LFP) is increasingly used to measure the combined activity of neurons within a region of tissue. Yet, available estimates of the size of this region are highly disparate, ranging from several hundred microns to a few millimeters. To measure the size of this region directly, we used a combination of multielectrode recordings and optical imaging. We determined the orientation selectivity of stimulus-evoked LFP signals in primary visual cortex and were able to predict it on the basis of the surrounding map of orientation preference. The results show that > 95% of the LFP signal originates within 250 microm of the recording electrode. This quantitative estimate indicates that LFPs are more local than often recognized and provides a guide to the interpretation of the increasing number of studies that rest on LFP recordings.

GABAA inhibition controls response gain in visual cortex.

GABAA inhibition is thought to play multiple roles in sensory cortex, such as controlling responsiveness and sensitivity, sharpening selectivity, and mediating competitive interactions. To test these proposals, we recorded in cat primary visual cortex (V1) after local iontophoresis of gabazine, the selective GABAA antagonist. Gabazine increased responsiveness by as much as 300%. It slightly decreased selectivity for stimulus orientation and direction, often by raising responses to all orientations. Strikingly, gabazine affected neither contrast sensitivity nor cross-orientation suppression, the competition seen when stimuli of different orientation are superimposed. These results were captured by a simple model in which GABAA inhibition has the same selectivity as excitation and keeps responses to unwanted stimuli below threshold. We conclude that GABAA inhibition in V1 helps enhance stimulus selectivity but is not responsible for competition among superimposed stimuli. It controls the sensitivity of V1 neurons by adjusting their response gain, without affecting their input gain.

The Detection of Visual Contrast in the Behaving Mouse

The mouse is becoming a key species for research on the neural circuits of the early visual system. To relate such circuits to perception, one must measure visually guided behavior and ask how it depends on fundamental stimulus attributes such as visual contrast. Using operant conditioning, we trained mice to detect visual contrast in a two-alternative forced-choice task. After 3–4 weeks of training, mice performed hundreds of trials in each session. Numerous sessions yielded high-quality psychometric curves from which we inferred measures of contrast sensitivity. In multiple sessions, however, choices were influenced not only by contrast, but also by estimates of reward value and by irrelevant factors such as recent failures and rewards. This behavior was captured by a generalized linear model involving not only the visual responses to the current stimulus but also a bias term and history terms depending on the outcome of the previous trial. We compared the behavioral performance of the mice to predictions of a simple decoder applied to neural responses measured in primary visual cortex of awake mice during passive viewing. The decoder performed better than the animal, suggesting that mice might not use optimally the information contained in the activity of visual cortex.

Temporal dynamics of neuronal modulation during exogenous and endogenous shifts of visual attention in macaque area MT

Dynamically shifting attention between behaviorally relevant stimuli in the environment is a key condition for successful adaptive behavior. Here, we investigated how exogenous (reflexive) and endogenous (voluntary) shifts of visual spatial attention interact to modulate activity of single neurons in extrastriate area MT. We used a double-cueing paradigm, in which the first cue instructed two macaque monkeys to covertly attend to one of three moving random dot patterns until a second cue, whose unpredictable onset exogenously captured attention, either signaled to shift or maintain the current focus of attention. The neuronal activity revealed correlates of both exogenous and endogenous attention, which could be well distinguished by their characteristic temporal dynamics. The earliest effect was a transient interruption of the focus of endogenous attention by the onset of the second cue. The neuronal signature of this exogenous capture of attention was a short-latency decrease of responses to the stimulus attended so far. About 70 ms later, the influence of exogenous attention leveled off, which was reflected in two concurrent processes: responses to the newly cued stimulus continuously increased because of allocation of endogenous attention, while, surprisingly, there was also a gradual rebound of attentional enhancement of the previously relevant stimulus. Only after an additional 110 ms did endogenous disengagement of attention from this previously relevant stimulus become evident. These patterns of attentional modulation can be most parsimoniously explained by assuming two distinct attentional mechanisms drawing on the same capacity-limited system, with exogenous attention having a much faster time course than endogenous attention.

Effects of Locomotion Extend throughout the Mouse Early Visual System

BACKGROUND Neural responses in visual cortex depend not only on sensory input but also on behavioral context. One such context is locomotion, which modulates single-neuron activity in primary visual cortex (V1). How locomotion affects neuronal populations across cortical layers and in precortical structures is not well understood. RESULTS We performed extracellular multielectrode recordings in the visual system of mice during locomotion and stationary periods. We found that locomotion influenced activity of V1 neurons with a characteristic laminar profile and shaped the population response by reducing pairwise correlations. Although the reduction of pairwise correlations was restricted to cortex, locomotion slightly but consistently increased firing rates and controlled tuning selectivity already in the dorsolateral geniculate nucleus (dLGN) of the thalamus. At the level of the eye, increases in locomotion speed were associated with pupil dilation. CONCLUSIONS These findings document further, nonmultiplicative effects of locomotion, reaching earlier processing stages than cortex.

Spatial integration in mouse primary visual cortex

Responses of many neurons in primary visual cortex (V1) are suppressed by stimuli exceeding the classical receptive field (RF), an important property that might underlie the computation of visual saliency. Traditionally, it has proven difficult to disentangle the underlying neural circuits, including feedforward, horizontal intracortical, and feedback connectivity. Since circuit-level analysis is particularly feasible in the mouse, we asked whether neural signatures of spatial integration in mouse V1 are similar to those of higher-order mammals and investigated the role of parvalbumin-expressing (PV+) inhibitory interneurons. Analogous to what is known from primates and carnivores, we demonstrate that, in awake mice, surround suppression is present in the majority of V1 neurons and is strongest in superficial cortical layers. Anesthesia with isoflurane-urethane, however, profoundly affects spatial integration: it reduces the laminar dependency, decreases overall suppression strength, and alters the temporal dynamics of responses. We show that these effects of brain state can be parsimoniously explained by assuming that anesthesia affects contrast normalization. Hence, the full impact of suppressive influences in mouse V1 cannot be studied under anesthesia with isoflurane-urethane. To assess the neural circuits of spatial integration, we targeted PV+ interneurons using optogenetics. Optogenetic depolarization of PV+ interneurons was associated with increased RF size and decreased suppression in the recorded population, similar to effects of lowering stimulus contrast, suggesting that PV+ interneurons contribute to spatial integration by affecting overall stimulus drive. We conclude that the mouse is a promising model for circuit-level mechanisms of spatial integration, which relies on the combined activity of different types of inhibitory interneurons.

Population Rate Dynamics and Multineuron Firing Patterns in Sensory Cortex

Cortical circuits encode sensory stimuli through the firing of neuronal ensembles, and also produce spontaneous population patterns in the absence of sensory drive. This population activity is often characterized experimentally by the distribution of multineuron “words” (binary firing vectors), and a match between spontaneous and evoked word distributions has been suggested to reflect learning of a probabilistic model of the sensory world. We analyzed multineuron word distributions in sensory cortex of anesthetized rats and cats, and found that they are dominated by fluctuations in population firing rate rather than precise interactions between individual units. Furthermore, cortical word distributions change when brain state shifts, and similar behavior is seen in simulated networks with fixed, random connectivity. Our results suggest that similarity or dissimilarity in multineuron word distributions could primarily reflect similarity or dissimilarity in population firing rate dynamics, and not necessarily the precise interactions between neurons that would indicate learning of sensory features.

Improving behavioral performance under full attention by adjusting response criteria to changes in stimulus predictability

One of the key features of active perception is the ability to predict critical sensory events. Humans and animals can implicitly learn statistical regularities in the timing of events and use them to improve behavioral performance. Here, we used a signal detection approach to investigate whether such improvements in performance result from changes of perceptual sensitivity or rather from adjustments of a response criterion. In a regular sequence of briefly presented stimuli, human observers performed a noise-limited motion detection task by monitoring the stimulus stream for the appearance of a designated target direction. We manipulated target predictability through the hazard rate, which specifies the likelihood that a target is about to occur, given it has not occurred so far. Analyses of response accuracy revealed that improvements in performance could be accounted for by adjustments of the response criterion; a growing hazard rate was paralleled by an increasing tendency to report the presence of a target. In contrast, the hazard rate did not affect perceptual sensitivity. Consistent with previous research, we also found that reaction time decreases as the hazard rate grows. A simple rise-to-threshold model could well describe this decrease and attribute predictability effects to threshold adjustments rather than changes in information supply. We conclude that, even under conditions of full attention and constant perceptual sensitivity, behavioral performance can be optimized by dynamically adjusting the response criterion to meet ongoing changes in the likelihood of a target.

Visual attention: of features and transparent surfaces

A recent report by Wannig et al. demonstrated the effects of selectively attending to individual surfaces in transparent motion patterns on neurons in the middle temporal area of awake, behaving monkeys. The study illustrates a highly adaptive and flexible attentional modulation of sensory responses.

Visual cortical networks: of mice and men

The visual cortical network consists of a number of specialized areas that are connected in a highly structured way. Understanding the function of this network is a milestone goal of visual neuroscience. This goal is pursued at different levels of description, including large-scale neuroanatomical as well as molecular and cellular perspectives. As a consequence, visual cortical networks are studied with a diverse set of methods across the order of mammalian species, ranging from the human all the way down to the mouse. Remarkable progress has been made at both ends of the spectrum. On the basis of work in humans, the last decade has seen ongoing refinements of the intricate functional organization of the cortical visual network. Neuroimaging studies have opened up the possibility to map individual visual areas, characterize their function and, search for an overarching organizational principle. Meanwhile, the mouse has become a valuable model system for early visual processing. A number of studies have demonstrated that basic response properties observed in higher-order mammals are also present in the mouse, making it possible to apply genetic tools to study visual network function. Here, we discuss the progress in these two fields side-by-side. We summarize new findings that have shaped our current understanding of the human cortical network. In addition, we review recent work that has laid the foundation for a mouse model of visual cortical processing. Although their brains are different, the visual cortical networks of mice and men share structural and functional principles.