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Open Access Publications from the University of California

Scholarly Works (6 results)

  • Article
  • Peer Reviewed
UC San Diego Previously Published Works (2019)
Most studies that focus on understanding how top-down knowledge influences behavior attempt to manipulate either 'attention' or 'expectation' and often use the terms interchangeably. However, having expectations about statistical regularities in the environment and the act of willfully allocating attention to a subset of relevant sensory inputs are logically distinct processes that could, in principle, rely on similar neural mechanisms and influence information processing at the same stages. In support of this framework, several recent studies attempted to isolate expectation from attention, and advanced the idea that expectation and attention both modulate early sensory processing. Here, we argue that there is currently insufficient empirical evidence to support this conclusion, because previous studies have not fully isolated the effects of expectation and attention. Instead, most prior studies manipulated the relevance of different sensory features, and as a result, few existing findings speak directly to the potentially separable influences of expectation and attention on early sensory processing. Indeed, recent studies that attempt to more strictly isolate expectation and attention suggest that expectation has little influence on early sensory responses and primarily influences later 'decisional' stages of information processing.
    Cover page: Dissociating the impact of attention and expectation on early sensory processing
    • Thesis
    • Peer Reviewed
    UC San Diego Electronic Theses and Dissertations (2020)

    Our visual world is full of ambiguous sensory signals, from which we have to extract relevant and meaningful information in order to guide optimal actions. To maximize the efficiency of this process, our visual system relies on foreknowledge to prioritize the processing of relevant or expected features. Knowledge of statistical regularities in the environment can lead to faster detection and recognition of objects when they are encountered in an expected context (e.g., a bird in a backyard) than when they are encountered in unlikely context (e.g., a bird in a washing machine). In addition, knowledge about the current task goals can also support faster and more accurate processing of relevant over irrelevant items--a mechanism referred to as selective attention. In what manner do these “top down” modulatory factors individually and jointly affect visual sensory processing, decision making, and behavior? In three studies, we examined how perceptual decision making is modulated by prior expectation about stimulus probabilities alone and in the context where knowledge about the current behavioral goals were available. We examined these effects both neurally via electroencephalography (EEG) and behaviorally through psychophysics and also in amnesic patients in relation to age-matched controls. To this end, we first devised an experimental paradigm where prior expectation and selective attention could be individually manipulated. The behavioral readouts from this paradigm were continuous which made it possible for the temporal evolution of the effects of expectation and attention on decision process to be probed both behaviorally and in relation to the continuous neural (EEG) measures. We first demonstrated that prior expectation improves decision processes by primarily affecting post-perceptual operations such as initiation and execution of motor responses, instead of directly improving the efficiency of early sensory processing. This finding confirms an idea that has been put forth by traditional theoretical framework that prior expectation affects decision making by preferentially modulating motor responses that correspond to sensory inputs with high probability of occurring. Further, we showed that while both expectation and attention improved behavior, the underlying neural mechanisms that give rise to these effects differed: while attention operates on the early processing of sensory inputs, expectation affects the late stage of decision making by biasing motor responses towards the most likely decision choice. These differential temporal dynamics of expectation and attention were observed bot h behaviorally and neurally. Finally, we demonstrated that an ability to utilize knowledge about current task goals and to form expectation based on statistical regularities of the sensory environment can be independent of a declarative memory system.

      Cover page: Neural dynamics of probabilistic perceptual decision making in the human brain
      • Article
      • Peer Reviewed
      UC San Diego Previously Published Works (2019)
      Prior knowledge about the probabilistic structure of visual environments is necessary to resolve ambiguous information about objects in the world. Expectations based on stimulus regularities exert a powerful influence on human perception and decision making by improving the efficiency of information processing. Another type of prior knowledge, termed top-down attention, can also improve perceptual performance by facilitating the selective processing of relevant over irrelevant information. While much is known about attention, the mechanisms that support expectations about statistical regularities are not well-understood. The hippocampus has been implicated as a key structure involved in or perhaps necessary for the learning of statistical regularities, consistent with its role in various kinds of learning and memory. Here, we tested this hypothesis using a motion discrimination task in which we manipulated the most likely direction of motion, the degree of attention afforded to the relevant stimulus, and the amount of available sensory evidence. We tested memory-impaired patients with bilateral damage to the hippocampus and compared their performance with controls. Despite a modest slowing in response initiation across all task conditions, patients performed similar to controls. Like controls, patients exhibited a tendency to respond faster and more accurately when the motion direction was more probable, the stimulus was better attended, and more sensory evidence was available. Together, these findings demonstrate a robust, hippocampus-independent capacity for learning statistical regularities in the sensory environment in order to improve information processing.
        Cover page: Preserved capacity for learning statistical regularities and directing selective attention after hippocampal lesions
        • Article
        • Peer Reviewed
        UC San Diego Previously Published Works (2018)
        Two factors play important roles in shaping perception: the allocation of selective attention to behaviorally relevant sensory features, and prior expectations about regularities in the environment. Signal detection theory proposes distinct roles of attention and expectation on decision-making such that attention modulates early sensory processing, whereas expectation influences the selection and execution of motor responses. Challenging this classic framework, recent studies suggest that expectations about sensory regularities enhance the encoding and accumulation of sensory evidence during decision-making. However, it is possible, that these findings reflect well documented attentional modulations in visual cortex. Here, we tested this framework in a group of male and female human participants by examining how expectations about stimulus features (orientation and color) and expectations about motor responses impacted electroencephalography (EEG) markers of early sensory processing and the accumulation of sensory evidence during decision-making (the early visual negative potential and the centro-parietal positive potential, respectively). We first demonstrate that these markers are sensitive to changes in the amount of sensory evidence in the display. Then we show, counter to recent findings, that neither marker is modulated by either feature or motor expectations, despite a robust effect of expectations on behavior. Instead, violating expectations about likely sensory features and motor responses impacts posterior alpha and frontal theta oscillations, signals thought to index overall processing time and cognitive conflict. These findings are inconsistent with recent theoretical accounts and suggest instead that expectations primarily influence decisions by modulating post-perceptual stages of information processing.SIGNIFICANCE STATEMENT Expectations about likely features or motor responses play an important role in shaping behavior. Classic theoretical frameworks posit that expectations modulate decision-making by biasing late stages of decision-making including the selection and execution of motor responses. In contrast, recent accounts suggest that expectations also modulate decisions by improving the quality of early sensory processing. However, these effects could instead reflect the influence of selective attention. Here we examine the effect of expectations about sensory features and motor responses on a set of electroencephalography (EEG) markers that index early sensory processing and later post-perceptual processing. Counter to recent empirical results, expectations have little effect on early sensory processing but instead modulate EEG markers of time-on-task and cognitive conflict.
          Cover page: Expectations Do Not Alter Early Sensory Processing during Perceptual Decision-Making
          • Article
          • Peer Reviewed
          UC San Diego Previously Published Works (2019)
          A chimera state is a spatiotemporal pattern of broken symmetry, where synchrony (coherent state) and asynchrony (incoherent state) coexist. Here, we report chimera states in electrocorticography recordings preceding, by several hours, each of seven seizures in one patient with epilepsy. Before the seizures, the onset channels are not synchronized, while the remaining channels are synchronized. During the seizures, this pattern of behavior flips and the nononset channels show a more asynchronous behavior. At a seizure offset, synchrony can be observed that might facilitate termination.
            Cover page: Cortical chimera states predict epileptic seizures.
            • Article
            • Peer Reviewed
            UC San Diego Previously Published Works (2022)
            Dynamic functional brain connectivity facilitates adaptive cognition and behaviour. Abnormal alterations within such connectivity could result in disrupted functions observed across various neurological conditions. As one of the most common neurological disorders, epilepsy is defined by the seemingly random occurrence of spontaneous seizures. A central but unresolved question concerns the mechanisms by which extraordinarily diverse propagation dynamics of seizures emerge. Here, we applied a graph-theoretical approach to assess dynamic reconfigurations in the functional brain connectivity before, during and after seizures that display heterogeneous propagation patterns despite sharing similar cortical onsets. We computed time-varying functional brain connectivity networks from human intracranial recordings of 67 seizures (across 14 patients) that had a focal origin-49 of these focal seizures remained focal and 18 underwent a bilateral spread (focal to bilateral tonic-clonic seizures). We utilized functional connectivity networks estimated from interictal periods across patients as control. Our results characterize network features that quantify the underlying functional dynamics associated with the observed heterogeneity of seizure propagation across these two types of focal seizures. Decoding these network features demonstrate that bilateral propagation of seizure activity is an outcome of the imbalance of global integration and segregation in the brain prior to seizure onset. We show that there exist intrinsic network signatures preceding seizure onset that are associated with the extent to which an impending seizure will propagate throughout the brain (i.e. staying within one hemisphere versus spreading transcallosally). Additionally, these features characterize an increase in segregation and a decrease in excitability within the brain network (i.e. high modularity and low spectral radius). Importantly, seizure-type-specific differences in these features emerge several minutes prior to seizure onset, suggesting the potential utility of such measures in intervention strategies. Finally, our results reveal network characteristics after the onset that are unique to the propagation mechanisms of two most common focal seizure subtypes, indicative of distinct reconfiguration processes that may assist termination of each seizure type. Together, our findings provide insights into the relationship between the temporal evolution of seizure activity and the underlying functional connectivity dynamics. These results offer exciting avenues where graph-theoretical measures could potentially guide personalized clinical interventions for epilepsy and other neurological disorders in which extensive heterogeneity is observed across subtypes as well as across and within individual patients.
              Cover page: Brain network dynamics codify heterogeneity in seizure evolution
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