Stimulus-choice (mis)alignment in primate area MT.

For stimuli near perceptual threshold, the trial-by-trial activity of single neurons in many sensory areas is correlated with the animal's perceptual report. This phenomenon has often been attributed to feedforward readout of the neural activity by the downstream decision-making circuits. The interpretation of choice-correlated activity is quite ambiguous, but its meaning can be better understood in the light of population-wide correlations among sensory neurons. Using a statistical nonlinear dimensionality reduction technique on single-trial ensemble recordings from the middle temporal (MT) area during perceptual-decision-making, we extracted low-dimensional latent factors that captured the population-wide fluctuations. We dissected the particular contributions of sensory-driven versus choice-correlated activity in the low-dimensional population code. We found that the latent factors strongly encoded the direction of the stimulus in single dimension with a temporal signature similar to that of single MT neurons. If the downstream circuit were optimally utilizing this information, choice-correlated signals should be aligned with this stimulus encoding dimension. Surprisingly, we found that a large component of the choice information resides in the subspace orthogonal to the stimulus representation inconsistent with the optimal readout view. This misaligned choice information allows the feedforward sensory information to coexist with the decision-making process. The time course of these signals suggest that this misaligned contribution likely is feedback from the downstream areas. We hypothesize that this non-corrupting choice-correlated feedback might be related to learning or reinforcing sensory-motor relations in the sensory population

Characterising feedback to mid-level visual cortex during perceptual decision-making

A long-standing question in neuroscience is how the activity of visual neurons supports perception. Historically examined from a purely feedforward perspective, this approach documented neuronal selectivity for specific perceptual features, sensitivity akin to an animal’s perceptual sensitivity and demonstrated causal effects of sensory neurons on an animal’s decision. Indeed, even the variable activity of single sensory neurons was found to be correlated with the decision an animal would make, often referred to as ‘choice probability’. This decision-related activity was long interpreted as reflecting the causal effect of feedforward noise on the decision process, but increasing evidence has pointed to a feedback origin of these correlations with behaviour. However the role of that such feedback remains unclear. The work in this thesis sought to investigate the nature of this feedback in order to help explain what it’s potential role in perceptual-decision making may be, as well as to further clarify long-held beliefs on the origin of decision-related activity. To do so, we focussed on the mechanisms underlying disparity perception in disparity-selective mid-level visual areas. First, we tested whether neurons in area V2 were causally involved in a disparity discrimination task. By electrically stimulating disparity-selective V2 neurons, we demonstrated a bias in the animals’ decisions in line with the preference of the stimulated neurons, suggesting a causal role for these neurons in disparity perception. We then proceeded to better characterise the feedback that gives rise to decision-related activity in these neurons, as well as another group of disparity-selective neurons in V3/V3a. Since feedback has often been assumed to selectively target visual neurons based on their relevance for the task or stimulus demands, we aimed to test the extent of this selectivity. To do so, we employed a novel task combining disparity discrimination with a spatial attention component, wherein animals had to ignore one stimulus whilst discriminating the other. Critically, this led to distinct predictions for decision-related activity depending on how selective the feedback would be. We found that decision-related activity could be observed for neurons representing an ignored task-irrelevant stimulus, incompatible with accounts of feedback which exclusively target task-relevant neurons. Our findings suggest that decision-related activity arises predominantly as a result of feedback targeting neurons selective for disparity, regardless of whether they contribute to the task. Importantly they imply a biological constraint to the selectivity of feedback, and demand a revision of current theoretical accounts of feedback in perceptual decision-making. The work presented here thus not only contributes to our understanding of disparity perception, but has critical implications for how feedback modulates the responses of visual neurons and ultimately shapes perception

The Generation of Complex Reaches

The study of motor cortex (dorsal premotor cortex and primary motor cortex) has been greatly aided by the development of a conceptual paradigm that has emerged over the past decade. In contrast to established frameworks, which view neural activity within motor cortex as a representation of particular movement parameters, the ‘dynamical systems paradigm’ posits that motor cortex is best understood via the low-dimensional neural processes that allow the generation of motor commands. This framework largely evolved from, and has been most successfully applied to, simple reaching tasks, where the sequential stages of movement generation are largely separated in time – motor cortex absorbs an input that specifies the identity of the upcoming reach, a second input initiates the movement, and strong, autonomous dynamics generate time-varying motor commands. However, while the dynamical systems paradigm has provided a useful scaffolding for interrogating motor cortex, our understanding of the mechanisms that generate movement is still evolving, and many questions remain unanswered. Prior work has established that the neural processes within motor cortex that generate descending commands are initiated by a large, condition-invariant input. But are movements made under different behavioral contexts initiated via the same mechanisms? Lesion studies suggest that the generation of so-called ‘self-initiated movements’ is uniquely dependent on the supplementary motor area (SMA), a premotor region immediately upstream of motor cortex. In contrast, SMA is thought to be less critical for generating externally-cued movements. To characterize the degree to which SMA is able to impact movement initiation across behavioral contexts, we trained two monkeys to make reaches that were either internally or externally cued. On a subset of trials, we disrupted activity within SMA via microstimulation and asked how this perturbation impacted the monkeys’ behavior. Surprisingly, we found that the effect of stimulation was largely preserved across contexts; the behavioral effects of stimulation could be explained by a simple model in which a context-invariant, time-varying kernel multiplicatively altered the odds of movement initiation. These results suggest that SMA is able to impact movement initiation across behavioral contexts. The question of how sequences of discrete actions are generated has been investigated for over one hundred years. It is commonly thought that once a given sequence (particularly a rapid sequence) becomes well-learned, individual actions that were once produced separately become ‘merged’, such that multiple actions are generated as a single, holistic unit. But what does it mean to generate multiple actions as a single unit? The dynamical systems paradigm offers the ability to translate this notion into specific predictions about the timing and structure of neural activity within motor cortex during sequence production. Importantly, it also offers predictions for the alternative hypothesis – that motor cortex generates the component actions of a sequence independently. To determine whether the production of rapid sequences requires motor cortex to merge multiple actions into a single ‘movement’, we trained monkeys to make sequences of two reaches. Surprisingly, we found that the same set of neural events are used to produce rapid sequences and isolated reaches. Rather than merging individual actions into a single unit, motor cortex generated rapid sequences by overlapping the neural activity related to reach preparation and execution. These results demonstrate that the performance of extremely fast, well-learned movement sequences does not require motor cortex to implement a sequence-specific strategy; the same neural motif that produces a simple reach can also generate movement sequences

Cortical Population Dynamics Underlying Choice, Reaction Time, and Confidence

Decision-making is a fundamental aspect of behavior that humans perform ubiquitously and repeatedly throughout their lives. Some decisions are second nature, like deciding to attend class, while others are complex, requiring an abundance of information to consider, such as the decision of which university to attend. However, all decision-making processes share core attributes that encompass the spectrum of complexity. Over the last several decades, scientists have identified and probed these characteristics to unveil the computational and neural underpinnings that make decision-making possible. In addition, these advances have pushed our understanding in other cognitive domains, including perception, attention, memory, learning, reward processing, and others. The essential nature of decision-making has provided an avenue for investigating and comprehending complex cognitive functions at a mechanistic level. The research laid out in this dissertation addresses the neural representation of evidence for a decision, its temporal dynamics and spatial distribution across two levels of the cortical hierarchy, and how it predicts three key behavioral manifestations: choice, reaction time, and confidence. Chapter One presents a general introduction of the perceptual decision-making field both from a behavioral and neurophysiological perspective. Chapter Two describes the novel behavioral paradigm I developed and the main two models I considered throughout this work. Chapter Three summarizes my findings in visual areas MT/MST and neural correlates of choice and confidence. In Chapter Four I detail my electrophysiological results from area LIP, suggesting a parallel strategy for simultaneous reporting of choice and confidence. Lastly, Chapter Five provides a systematic analysis of the training process used to prepare animals for the experiments, elucidating interesting possible theories for learning. All in all, this work demonstrates both the strengths and limitations of current theories within the framework of bounded evidence accumulation, bringing us closer to a comprehensive account of decision formation and confidence judgments