Faculty Bibliography

Prediction of future sensory input based on past sensory information is essential for organisms to effectively adapt their behavior in dynamic environments. Humans successfully predict future stimuli in various natural settings. Yet, it remains elusive how the brain achieves effective prediction despite enormous variations in sensory input rate, which directly affect how fast sensory information can accumulate. We presented participants with acoustic sequences capturing temporal statistical regularities prevalent in nature and investigated neural mechanisms underlying predictive computation using MEG. By parametrically manipulating sequence presentation speed, we tested two hypotheses: neural prediction relies on integrating past sensory information over fixed time periods or fixed amounts of information. We demonstrate that across halved and doubled presentation speeds, predictive information in neural activity stems from integration over fixed amounts of information. Our findings reveal the neural mechanisms enabling humans to robustly predict dynamic stimuli in natural environments despite large sensory input rate variations.

A degraded, black-and-white image of an object, which appears meaningless on first presentation, is easily identified after a single exposure to the original, intact image. This striking example of perceptual learning reflects a rapid (one-trial) change in performance, but the kind of learning that is involved is not known. We asked whether this learning depends on conscious (hippocampus-dependent) memory for the images that have been presented or on an unconscious (hippocampus-independent) change in the perception of images, independently of the ability to remember them. We tested five memory-impaired patients with hippocampal lesions or larger medial temporal lobe (MTL) lesions. In comparison to volunteers, the patients were fully intact at perceptual learning, and their improvement persisted without decrement from 1 d to more than 5 mo. Yet, the patients were impaired at remembering the test format and, even after 1 d, were impaired at remembering the images themselves. To compare perceptual learning and remembering directly, at 7 d after seeing degraded images and their solutions, patients and volunteers took either a naming test or a recognition memory test with these images. The patients improved as much as the volunteers at identifying the degraded images but were severely impaired at remembering them. Notably, the patient with the most severe memory impairment and the largest MTL lesions performed worse than the other patients on the memory tests but was the best at perceptual learning. The findings show that one-trial, long-lasting perceptual learning relies on hippocampus-independent (nondeclarative) memory, independent of any requirement to consciously remember.

Biological motions commonly contain multiple frequency components in which each fundamental has to be adjusted by motor learning to acquire a new motor skill or maintain acquired skills. At times during this motor performance one frequency component needs to be enhanced (gain-up) while another is suppressed (gain-down). This pattern of simultaneous gain-up and -down adjustments at different frequencies is called frequency competitive motor learning. Currently we investigated cerebellar roles in this behavior utilizing the goldfish vestibulo-ocular reflex (VOR). Previously, VOR motor learning was shown in primates to be frequency selective and exhibit frequency competitive motor learning. Here we demonstrate that the goldfish VOR performs frequency competitive motor learning when high and low frequency components are trained to gain-up and gain-down, respectively. However, when the two frequency components were trained in the opposite directions only gain-up component was observed. We also found that cerebellectomy precluded any frequency competitive VOR motor learning. Complementary single unit recordings from vestibulo-cerebellar Purkinje cells revealed changes in firing modulation along with gain-down learning, but not with gain-up learning irrespective of frequency. These results demonstrate that the cerebellum is required for all frequency competitive VOR motor learning and Purkinje cell activity therein is well correlated with all gain-down behaviors independent of frequency. However, frequency competitive gain-up learning requires intact, recursive brainstem/cerebellar pathways. Collectively these findings support the idea that VOR gain-up and gain-down learning utilize separate brainstem/cerebellar circuitry that, in turn, clearly underlies the unique ability of the oculomotor system to deal with multiple frequency components.

Memories of the images that we have seen are thought to be reflected in the reduction of neural responses in high-level visual areas such as inferotemporal (IT) cortex, a phenomenon known as repetition suppression (RS). We challenged this hypothesis with a task that required rhesus monkeys to report whether images were novel or repeated while ignoring variations in contrast, a stimulus attribute that is also known to modulate the overall IT response. The monkeys' behavior was largely contrast invariant, contrary to the predictions of an RS-inspired decoder, which could not distinguish responses to images that are repeated from those that are of lower contrast. However, the monkeys' behavioral patterns were well predicted by a linearly decodable variant in which the total spike count was corrected for contrast modulation. These results suggest that the IT neural activity pattern that best aligns with single-exposure visual recognition memory behavior is not RS but rather sensory referenced suppression: reductions in IT population response magnitude, corrected for sensory modulation.

Neuronal oscillations route external and internal information across brain regions. In the olfactory system, the two central nodes-the olfactory bulb (OB) and the piriform cortex (PC)-communicate with each other via neural oscillations to shape the olfactory percept. Communication between these nodes have been well characterized in non-human animals but less is known about their role in the human olfactory system. Using a recently developed and validated EEG-based method to extract signals from the OB and PC sources, we show in healthy human participants that there is a bottom-up information flow from the OB to the PC in the beta and gamma frequency bands, while top-down information from the PC to the OB is facilitated by delta and theta oscillations. Importantly, we demonstrate that there was enough information to decipher odor identity above chance from the low gamma in the OB-PC oscillatory circuit as early as 100 ms after odor onset. These data further our understanding of the critical role of bidirectional information flow in human sensory systems to produce perception. However, future studies are needed to determine what specific odor information is extracted and communicated in the information exchange.

Background: A prominent feature of addiction is the tendency to exploit a previously rewarding resource despite its diminishing returns. Such behavior is aptly captured in animal foraging models that have recently been extended to humans. Catecholaminergic systems are thought to underlie such behavior, but a precise empirical account of this is lacking in humans.
Method(s): We recruited 21 treatment-seeking individuals with opioid use disorder (OUD) and 21 socio-demographically matched controls. Participants completed a patch foraging task, during which they made sequential decisions between "harvesting" a depleting source of rewards or incurring a travel cost to harvest a replenished resource. We further acquired high-resolution (<0.7mm in-plane) neuromelanin-sensitive MRI scans, which reliably probes long-term dopamine and norepinephrine function, in a subset (n=27) of participants. Our imaging protocol separately localized dopaminergic nuclei (SN/VTA) and the noradrenergic LC, which have been theoretically linked to foraging behavior and are implicated in addiction.
Result(s): Behaviorally, OUD participants over-harvested more than controls and showed insensitivity to travel times (travel time effect: p=0.79). These group differences held when controlling for age, sex and cognitive variables. Over-harvesting scaled with increased years of opioid use (OUD; r=-0.51, p=0.03). Our imaging analysis revealed a dissociation whereby, across participants, over-harvesting was associated with lower neuromelanin signal contrast in dopaminergic nuclei (SN/VTA, rho=0.40, p=0.04), but not in LC (p=0.55).
Conclusion(s): Our findings suggest that individual differences in foraging behavior are related to interindividual variability in dopaminergic-but not noradrenergic-circuit function that informs reward rates in dynamic decision environments and may serve as a marker for maladaptive reward-seeking behavior. Supported By: Busch Biomedical Research Grant Keywords: Addiction, Foraging, Dopamine, Neuromelanin-Sensitive MRI
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During the development of the vertebrate nervous systems, genetic programs assemble an immature circuit that is subsequently refined by neuronal activity evoked by external stimuli. However, prior to sensory experience, the intrinsic property of the developing nervous system also triggers correlated network-level neuronal activity, with retinal waves in the developing vertebrate retina being the best documented example. Spontaneous activity has also been found in the visual system of Drosophila Here, we compare the spontaneous activity of the developing visual system between mammalian and Drosophila and suggest that Drosophila is an emerging model for mechanistic and functional studies of correlated spontaneous activity.