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Attention selectively routes the most behaviorally relevant information from the stream of sensory inputs through the hierarchy of cortical areas. Previous studies have shown that visual attention depends on the phase of oscillatory brain activities. These studies mainly focused on the stimulus presentation period, rather than the pre-stimulus period. Here, we hypothesize that selective attention controls the phase of oscillatory neural activities to efficiently process relevant information. We document an attentional modulation of pre-stimulus inter-trial phase coherence (a measure of deviation between instantaneous phases of trials) of low frequency local field potentials (LFP) in visual area MT of macaque monkeys. Our data reveal that phase coherence increases following a spatial cue deploying attention towards the receptive field of the recorded neural population. We further show that the attentional enhancement of phase coherence is positively correlated with the modulation of the stimulus-induced firing rate, and importantly, a higher phase coherence is associated with a faster behavioral response. These results suggest a functional utilization of intrinsic neural oscillatory activities for an enhanced processing of upcoming stimuli.

In our everyday lives, we receive information from our environment and respond to this received information by performing motor actions. A transformation between sensory information and motor action that is not a mere reflex, occurs inside our brain. Most of our goal-directed behavior involves this transformation, which may become impaired in different neurological and psychiatric disorders such as Parkinson’s disease. Therefore, it becomes important to know where and how this transformation happens in the brain. I trained mice in a whisker-based selective detection task to discover mechanisms of the sensory-motor transformation. In this type of behavior, mice learned to selectively respond to a brief whisker stimulation by licking a waterspout. Using widefield calcium imaging during task performance, my colleagues revealed regions in the cortex that became active during sensory and motor behavior. I performed whisker imaging to give insights about the mouse behavior as well as verifying the temporal limitations of widefield calcium imaging using recordings of local field potentials (Chapter 2). Among active regions in frontal cortex, I localized the site of transformation to the whisker motor cortex using single unit recording and advanced data analysis (Chapter 3). Importantly, I discovered a subcortical site of sensory-motor transformation in the dorsolateral striatum, residing down-stream of the whisker motor cortex (Chapter 4). Thus, my research describes a network composed of cortical and subcortical regions involved in sensory-motor transformation. Our findings may contribute towards developing therapeutics that target the motor cortex and dorsolateral striatum in health conditions that impair these regions and sensory and motor behavior in general.

Goal-directed behavior paradigms inevitably involve temporal processes, such as anticipation, expectation, timing, waiting, and withholding. And yet, amongst the vast use of object-based task paradigms, characterizations of temporal features are often neglected. Here, we longitudinally analyzed mice from naive to expert performance in a somatosensory selective detection task. In addition to tracking standard measures from signal detection theory, we also characterized learning of temporal features. We find that mice transition from general sampling strategies to stimulus detection and stimulus discrimination. During these transitions, mice learn to wait as they anticipate an expected stimulus presentation and to time their response after a stimulus presentation. By establishing and implementing standardized measures, we show that the development of waiting and timing in the task overlaps with learning of stimulus detection and discrimination. We also investigated sex differences in temporal and object-based trajectories of learning, finding that males learn strategies idiosyncratically and that females learn strategies more sequentially and stereotypically. Overall, our findings emphasize multiple temporal strategies in learning for an object-based task and highlight the importance of considering diverse temporal and object-based features when characterizing behavioral and neuronal aspects of learning.Competing Interest StatementThe authors have declared no competing interest.

The amygdala and hippocampus are central to emotional processing, yet the transient neural dynamics coordinating these regions remain unclear. We simultaneously recorded single-neuron activity and local field potentials from both regions in epilepsy patients during an emotional image-rating task. Neurons in both regions responded to images with firing rate changes that predicted subjective ratings of extreme pleasantness or unpleasantness. To examine the underlying oscillatory mechanisms, we analyzed beta bursts (13-30 Hz)-transient, high-power events-since conventional spectral analyses revealed no valence-specific patterns. Beta bursts were associated with increased gamma amplitude and enhanced phase coherence in both structures, with beta-gamma phase-amplitude coupling capturing emotion-related dynamics. Critically, amygdala beta bursts strongly suppressed hippocampal firing through interneuron activation during negative valence processing, whereas hippocampal bursts showed no reciprocal influence. These findings suggest that beta bursts provide a temporal code for emotion and represent a candidate mechanism for targeted neuromodulation in mood disorders.

A learned sensory-motor behavior engages multiple brain regions, including the neocortex and the basal ganglia. How a target stimulus is selected by these regions remains poorly understood. Here, we performed electrophysiological recordings and pharmacological inactivations of motor cortex and dorsolateral striatum to determine the representations within and functions of each region during performance in a selective whisker detection task in male and female mice. From the recording experiments, peak pre-response activity and significant choice probability emerged in the motor cortex before the dorsolateral striatum, suggesting a sensory-to-motor transformation in which the striatum is downstream of motor cortex. We performed pharmacological inactivation studies to determine the necessity of these brain regions for this task. We found that suppressing the dorsolateral striatum, but not motor cortex, severely disrupts responding to task-relevant stimuli, without disrupting the ability to respond. Together these data support the dorsolateral striatum, and not motor cortex, as an essential node in the sensory-to- motor transformation of this whisker detection task. We learn to do various sensory-motor behavior in our daily life, such as clicking on a journal article that looks interesting, among other articles. There are parts of our brain that are active when we do these learned behaviors, such as motor cortex and basal ganglia. But what is the order of activation of these regions? Which of them is necessary for responding to task-relevant sensory information? To answer these questions, we trained mice in a whisker-based target selection task and used recording of neural activity and inactivation of subregions within motor cortex and basal ganglia in expert mice. Our findings show dorsolateral striatum, a region within basal ganglia, is a bottleneck for performing task-related sensory-to-motor transformation.

Responding to a stimulus requires transforming an internal sensory representation into an internal motor representation. Where and how this sensory-motor transformation occurs is a matter of vigorous debate. Here, we trained mice in a whisker detection go/no-go task in which they learned to respond (lick) following a transient whisker deflection. Using single unit recordings, we quantified sensory-, motor- and choice-related activities in whisker primary somatosensory cortex (S1), whisker primary motor cortex (wMC) and anterior lateral motor cortex (ALM). Based on the criteria of having both strong sensory and motor representations and early choice probability, we identify whisker motor cortex as the cortical region most directly related to the sensory-motor transformation. Our data support a model of sensory amplification occurring between S1 and wMC, sensory-motor transformation occurring within wMC, and propagation of a motor command occurring between wMC and ALM. Competing Interest Statement The authors have declared no competing interest.

A learned sensory-motor behavior engages multiple brain regions, including the neocortex and the basal ganglia. How these brain regions coordinate to affect sensory selection (for target stimuli) and inhibition (for distractor stimuli) remains unknown. Here, we performed laminar electrophysiological recordings and muscimol inactivation in frontal cortex and dorsolateral striatum to determine the representations within and functions of each region during selective detection performance. From the recording experiments, in deep layers of frontal cortex and dorsolateral striatum we observed similar encoding of sensory and motor features. However, muscimol inactivation of each region resulted in drastically different outcomes. Inactivation of target-aligned striatum substantially reduced behavioral responses to all task stimuli without disrupting the ability to respond, suggesting essential roles in sensory selection. In contrast, inactivation of distractor-aligned frontal cortex increased responses to distractor stimuli, indicating essential roles in distractor inhibition. Overall, these data suggest distinct functions of frontal cortex and dorsolateral striatum in this task, despite having similar neuronal representations. Competing Interest Statement The authors have declared no competing interest.

Spontaneous neuronal activity strongly impacts stimulus encoding and behavioral responses. We sought to determine the effects of neocortical prestimulus activity on stimulus detection. We trained mice in a selective whisker detection task, in which they learned to respond (lick) to target stimuli in one whisker field and ignore distractor stimuli in the contralateral whisker field. During expert task performance, we used widefield Ca2+ imaging to assess prestimulus and post-stimulus neuronal activity broadly across frontal and parietal cortices. We found that lower prestimulus activity correlated with enhanced stimulus detection: lower prestimulus activity predicted response versus no response outcomes and faster reaction times. The activity predictive of trial outcome was distributed through dorsal neocortex, rather than being restricted to whisker or licking regions. Using principal component analysis, we demonstrate that response trials are associated with a distinct and less variable prestimulus neuronal subspace. For single units, prestimulus choice probability was weak yet distributed broadly, with lower than chance choice probability correlating with stronger sensory and motor encoding. These findings support a low amplitude, low variability, optimal prestimulus cortical state for stimulus detection that presents globally and predicts response outcomes for both target and distractor stimuli. Competing Interest Statement The authors have declared no competing interest.

An essential feature of goal-directed behavior is the ability to selectively respond to the diverse stimuli in one's environment. However, the neural mechanisms that enable us to respond to target stimuli while ignoring distractor stimuli are poorly understood. To study this sensory selection process, we trained male and female mice in a selective detection task in which mice learn to respond to rapid stimuli in the target whisker field and ignore identical stimuli in the opposite, distractor whisker field. In expert mice, we used widefield Ca2+ imaging to analyze target-related and distractor-related neural responses throughout dorsal cortex. For target stimuli, we observed strong signal activation in primary somatosensory cortex (S1) and frontal cortices, including both the whisker representation of primary motor cortex (wMC) and anterior lateral motor cortex (ALM). For distractor stimuli, we observe strong signal activation in S1, with minimal propagation to frontal cortex. Our data support only modest subcortical filtering, with robust, step-like attenuation in distractor processing between mono-synaptically coupled regions of S1 and wMC. This study establishes a highly robust model system for studying the neural mechanisms of sensory selection and places important constraints on its implementation.

Attention selectively routes the most behaviorally relevant information among the vast pool of sensory inputs through cortical regions. Previous studies have shown that visual attention samples the surrounding stimuli periodically. However, the neural mechanism underlying this sampling in the sensory cortex, and whether the brain actively uses these rhythms, has remained elusive. Here, we hypothesize that selective attention controls the phase of oscillatory synaptic activities to efficiently process the relevant information in the brain. We document an attentional modulation of pre-stimulus inter-trial phase coherence (a measure of deviation between instantaneous phases of trials) at low frequencies in macaque visual area MT. Our data reveal that phase coherence increases when attention is deployed towards the receptive field of the recorded neural population. We further show that the attentional enhancement of phase coherence is positively correlated with the attentional modulation of stimulus induced firing rate, and importantly, a higher phase coherence leads to a faster behavioral response. Our results suggest a functional utilization of intrinsic neural oscillatory activities for better processing upcoming environmental stimuli, generating the optimal behavior.