Browsing by Author "Glickfeld, Lindsey L"

Motor preparation is a key component in the control of movement. It allows higher-level cognitive factors, like expectation, to enhance the speed and accuracy of planned movements. Smooth pursuit eye movements are relatively simple, voluntary eye movements that allow ocular tracking of moving objects. Smooth pursuit eye movements are driven by an integration of two signals: visual motion and visual-motor gain. Here, we use smooth pursuit eye movement in macaque monkeys as a model sensorimotor behavior to examine how motor preparation is incorporated into neural circuits responsible for controlling movement. First, we developed a behavioral paradigm that allowed rapid adaptation of expectation and shed light on how expectation-related motor preparation could be incorporated into the smooth pursuit eye movement circuit. We used blocks of trials with different blends of target speeds to influence the pursuit system’s expectation of upcoming target speed; we estimated the effect of expectation with probe trials of equal speed across the different blocks of trials. Pursuit initiation during the probe trials was faster during blocks of trials where most trials presented relatively fast-moving versus slow-moving targets. Contextual modulation of eye speed during pursuit initiation had a larger effect for low-contrast targets, consistent with a Bayesian-like computation that estimates target speed by a reliability-weighted combination between expectation and sensory evidence. Importantly, a model that adjusts the gain of visual-motor transmission predicts the behavioral effects of speed expectation and target contrast. Second, we collected single unit neurophysiological data in the smooth eye movement region of the frontal eye fields (FEFsem) while monkeys tracked targets during the speed context paradigm. Expectation of target speed is encoded as preparatory ramps of firing rate in FEFsem during fixations in advance of any target or eye movement. Following target motion onset, the preparatory activity is used in a Bayesian-like decoding computation that estimates the speed of target motion as a combination of the preparatory activity and visual motion inputs weighted according to the reliability of visual motion. Third, we evaluated what effect preparatory modulation of activity in FEFsem has on visual-motor gain during motor preparation. At the population level, FEFsem preparatory activity ramps up along “output-potent” dimensions and in parallel with a preparatory-related modulation of visual-motor gain. Taken together, these findings suggest that the pursuit system uses a visual-motor gain signal, implemented by FEFsem, to incorporate expectation-related signals into preparation for impending visual motion and smooth pursuit eye movement. This preparatory signal both dials up gain in advance of any visual motion or eye movement and influences the gain that is set during initiation of pursuit in a Bayesian-like manner.

Vocal communication is a key behavior by which mammals form social bonds and convey information about social status and mating fitness. However, the cellular and synaptic nature of the neural circuits that adaptively regulate vocalization as a function of the individual’s social and environmental context remain unknown. Here, I helped pioneer the use of an intersectional genetic method to identify a subpopulation of neurons in the midbrain periaqueductal gray (PAG) of the mouse that act on downstream vocal-patterning circuits to gate ultrasonic courtship vocalizations. Next, I used transsynaptic tracing to identify two populations of inhibitory neurons that lie upstream of these PAG-USV neurons that exert opposing effects on USV production. I used molecular profiling, optogenetics, and circuit dissection in brain slices to establish that PAG-projecting GABAergic neurons in the preoptic hypothalamus promote USV production. In contrast, I found that PAG-projecting GABAergic neurons in the central-medial boundary zone of the amygdala suppress USV production without disrupting non-vocal social behavior. Finally, I used fiber photometry during free behaviors to reveal that affiliative social and sexual interactions excite USV-promoting preoptic neurons while innately aversive stimuli activate USV-suppressing amygdala neurons. These experiments provide an important step forward in mapping the brain-wide networks that regulate vocalizations as a function of social and environmental contexts.

Information about diverse visual features is encoded in distributed visual cortical areas. Which area/areas are required for perception for a given visual feature and how the encoded visual information is computed to guide visual perception are the main questions of this dissertation. Here I take advantage of the mouse visual system to tackle these questions. I first identify mouse visual cortical areas (primary visual cortex (V1) and higher visual areas (HVAs)) that are required for perception of different visual features via a combination of optogenetics and mouse psychophysics. I find that V1, LM (lateromedial) and AL (anterolateral) are required for discriminating orientation and detecting contrast. However, PM (posteromedial) is not involved in the orientation discrimination task. Instead, suppressing PM increases contrast detection threshold and consistently increases false alarm rate in both contrast and speed increment detection tasks. The effects of PM suppression on false alarm rate remain intact even when the visual stimuli are presented outside of the affected visual field, suggesting a non-visual specific role. To understand the computation that transforms sensory encoding to decision choice, I next use visual adaptation as a tool to determine a decoder adopted by the mouse to discriminate orientation (target versus. distractor orientation) via a combination of in vivo calcium imaging and modeling approaches. This decoder sums the neuronal population response suboptimally with higher positive weights biased towards target preferring neurons without negatively weighting the distractor preferring neurons. This decoder scheme could also be used for detecting contrast, serving as a potential reason why similar areas are required for both orientation discrimination and contrast detection tasks. To dissect the sensory and cognitive contribution of each area to the visual tasks, I attempt to use the sensitivity and bias measures from the Signal Detection Theory (SDT). However, both behavioral and neuronal evidence suggests that changes in bias can result from changes in sensory encoding, decision criterion or both, limiting the usage of SDT in dissociating two key components of perceptual decision-making process: sensory encoding versus decision criterion placement. Lastly, since adaptation can induce changes in sensory encoding and thus has profound perceptual consequences, I also apply in vivo extracellular single-unit recording in the mouse visual areas to characterize adaptation profiles. I observe a cascaded increase of adaptation along the geniculate visual pathway and much heterogeneity of adaptation within any recorded visual areas. In all, these serials of studies provide rich neuronal, behavioral and computational evidence to link between sensory encoding and perceptual behaviors.

Attentional modulation of neuronal activity in sensory cortex could alter perception by enhancing the local representation of attended stimuli or its behavioral read-out downstream. We tested these hypotheses using a task in which mice are cued on interleaved trials to attend visual or auditory targets. Neurons in primary visual cortex (V1) that encode task stimuli have larger visually-evoked responses when attention is directed toward vision. To determine whether the attention-dependent changes in V1 reflect changes in representation or read-out, we decoded task stimuli and choices from population activity. Surprisingly, both visual and auditory choices can be decoded from V1, but decoding takes advantage of unique activity patterns across modalities. Furthermore, decoding of choices, but not stimuli, is impaired when attention is directed toward the opposite modality. The specific effect on choice suggests behavioral improvements with attention are largely due to targeted read-out of the most informative V1 neurons.

An individual pyramidal cell receives thousands of inputs along its somato-dendritic axis. Thus, within a single pyramidal cell, great computational capacity can emerge not only from the sheer number of synapses, but also from the diverse nature of transmission at each site. Pre- and post-synaptic specializations enable spike activity to be conferred to the postsynaptic cell with specific sign, strength, and kinetics. How these properties of synaptic transmission ultimately shape cellular activity and circuit function is a fundamental question in the field of neuroscience. In my thesis work, I have used a variety of in vitro and in vivo electrophysiological approaches to study the activity of neurons in mouse visual cortex and the connections between them. I have identified synaptic mechanisms that determine temporal and spatial integration of visual stimuli, as well as a synaptic mechanism for specialization of higher-visual areas. Together, these results demonstrate that properties of synaptic transmission play a role in performing fundamental computations across many areas of visual cortex.