Many sensory systems adapt their input-output relationship to changes in the statistics of the ambient stimulus. Such adaptive behavior has been measured in a motion detection sensitive neuron of the fly visual system, H1. The rapid adaptation of the velocity response gain has been interpreted as evidence of optimal matching of the H1 response to the dynamic range of the stimulus, thereby maximizing its information transmission. Here, we show that correlation-type motion detectors, which are commonly thought to underlie fly motion vision, intrinsically possess adaptive properties. Increasing the amplitude of the velocity fluctuations leads to a decrease of the effective gain and the time constant of the velocity response without any change in the parameters of these detectors. The seemingly complex property of this adaptation turns out to be a straightforward consequence of the multidimensionality of the stimulus and the nonlinear nature of the system. insect ͉ model ͉ motion vision A daptation is a widespread phenomenon in biological systems. Generally it may be defined as a change in the sensitivity of the system to the current stimulus after a change in the statistics of the input signal, making the system better suited to cope with the present environment. In particular, the gain of the input-output relation of sensory systems is often modified, enabling them to convey information about the relevant stimulus parameters despite changes in the statistics of the sensory environment. Such adaptation has been observed in the well studied motion detection system that underlies fly motion vision (1-3). In the motion sensitive neuron, H1, the variance of a band-limited Gaussian velocity waveform affects the neuron's velocity response relationship. This response exhibits a rather steep slope around zero velocity for small velocity fluctuations, whereas for large velocity fluctuations this slope was found to be substantially reduced (4-6). Gain control in H1 has been interpreted as adaptive rescaling set to match the dynamic range of the response to that of the stimulus and used to maximize the system's information transmission. However, the mechanism underlying this adaptation has not been elucidated.Adaptation in sensory systems often occurs on a much slower time scale than the duration of the system's impulse response, indicating the presence of a special mechanism that slowly changes the system's response parameters integrating information about the stimulus history. H1 gain adaptation takes place on a surprisingly fast time scale: it occurs within 1 s after switching from one stimulus condition to another (5). Fast adaptation has also been observed in other neuronal sensory systems (7-9), not only in the response gain, but also in its time course (7). When the adaptation operates on the same time scale as the response itself, the separation between the mechanisms underlying the adaptation and those that give rise to the response becomes ambiguous, suggesting that the adaptation emerges naturally from the salient ...

Bilateral vestibulopathy (BVP) is defined as the impairment or loss of function of either the labyrinths or the eighth nerves. Patients with total BVP due to bilateral vestibular nerve section exhibit difficulties in spatial memory and navigation and show a loss of hippocampal volume. In clinical practice, most patients do not have a complete loss of function but rather an asymmetrical residual functioning of the vestibular system. The purpose of the current study was to investigate navigational ability and hippocampal atrophy in BVP patients with residual vestibular function. Fifteen patients with BVP and a group of age- and gender- matched healthy controls were examined. Self-reported questionnaires on spatial anxiety and wayfinding were used to assess the applied strategy of wayfinding and quality of life. Spatial memory and navigation were tested directly using a virtual Morris Water Maze Task. The hippocampal volume of these two groups was evaluated by voxel-based morphometry. In the patients, the questionnaire showed a higher spatial anxiety and the Morris Water Maze Task a delayed spatial learning performance. MRI revealed a significant decrease in the gray matter mid-hippocampal volume (Left: p = 0.006, Z = 4.58, Right: p < 0.001, Z = 3.63) and posterior parahippocampal volume (Right: p = 0.005, Z = 4.65, Left: p < 0.001, Z = 3.87) compared to those of healthy controls. In addition, a decrease in hippocampal formation volume correlated with a more dominant route-finding strategy. Our current findings demonstrate that even partial bilateral vestibular loss leads to anatomical and functional changes in the hippocampal formation and objective and subjective behavioral deficits.

Previous evidence indicates that the brain stores memory in two complementary systems, allowing both rapid plasticity and stable representations at different sites. For memory to be established in a long-lasting neocortical store, many learning repetitions are considered necessary after initial encoding into hippocampal circuits. To elucidate the dynamics of hippocampal and neocortical contributions to the early phases of memory formation, we closely followed changes in human functional brain activity while volunteers navigated through two different, initially unknown virtual environments. In one condition, they were able to encode new information continuously about the spatial layout of the maze. In the control condition, no information could be learned because the layout changed constantly. Our results show that the posterior parietal cortex (PPC) encodes memories for spatial locations rapidly, beginning already with the first visit to a location and steadily increasing activity with each additional encounter. Hippocampal activity and connectivity between the PPC and hippocampus, on the other hand, are strongest during initial encoding, and both decline with additional encounters. Importantly, stronger PPC activity related to higher memory-based performance. Compared with the nonlearnable control condition, PPC activity in the learned environment remained elevated after a 24-h interval, indicating a stable change. Our findings reflect the rapid creation of a memory representation in the PPC, which belongs to a recently proposed parietal memory network. The emerging parietal representation is specific for individual episodes of experience, predicts behavior, and remains stable over offline periods, and must therefore hold a mnemonic function.long-term memory | posterior parietal cortex | precuneus | memory systems consolidation | virtual reality L earning enables adaptive and effective interaction with the environment based on past experience. How this essential capability of the brain to encode, store, and later retrieve new information is implemented on the systems level has been the focus of many studies. However, although there is consistent evidence that specific brain regions are involved in learning and memory, the interactions between these regions and their temporal dynamics remain unclear. For declarative memory, one influential model proposes complementary roles of the hippocampus and neocortex in supporting memory representations (1-3). It assumes that the highly plastic hippocampus serves as a fast learner, transiently storing newly encountered information. Later on, this information is gradually integrated into more stable neocortical networks (4).Many experiments in animals and humans have confirmed decreased hippocampal but increased neocortical contributions to memory retrieval with longer consolidation intervals (5-7). Concerning the time frame during which hippocampal independence of a memory is established, accounts diverge widely. In the case of patients with medial temporal lobe (MTL) dama...