Dynamic categorization rules alter representations in human visual cortex.

Everyday perceptual tasks require sensory stimuli to be dynamically encoded and analyzed according to changing behavioral goals. For example, when searching for an apple at the supermarket, one might first find the Granny Smith apples by separating all visible apples into the categories "green" and "non-green". However, suddenly remembering that your family actually likes Fuji apples would necessitate reconfiguring the boundary to separate "red" from "red-yellow" objects. This flexible processing enables identical sensory stimuli to elicit varied behaviors based on the current task context. While this phenomenon is ubiquitous in nature, little is known about the neural mechanisms that underlie such flexible computation. Traditionally, sensory regions have been viewed as mainly devoted to processing inputs, with limited involvement in adapting to varying task contexts. However, from the standpoint of efficient computation, it is plausible that sensory regions integrate inputs with current task goals, facilitating more effective information relay to higher-level cortical areas. Here we test this possibility by asking human participants to visually categorize novel shape stimuli based on different linear and non-linear boundaries. Using fMRI and multivariate analyses of retinotopically-defined visual areas, we found that shape representations in visual cortex became more distinct across relevant decision boundaries in a context-dependent manner, with the largest changes in discriminability observed for stimuli near the decision boundary. Importantly, these context-driven modulations were associated with improved categorization performance. Together, these findings demonstrate that codes in visual cortex are adaptively modulated to optimize object separability based on currently relevant decision boundaries.

Brain network dynamics codify heterogeneity in seizure evolution.

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.

Intermittent brain network reconfigurations and the resistance to social media influence.

Since its development, social media has grown as a source of information and has a significant impact on opinion formation. Individuals interact with others and content via social media platforms in a variety of ways, but it remains unclear how decision-making and associated neural processes are impacted by the online sharing of informational content, from factual to fabricated. Here, we use EEG to estimate dynamic reconfigurations of brain networks and probe the neural changes underlying opinion change (or formation) within individuals interacting with a simulated social media platform. Our findings indicate that the individuals who changed their opinions are characterized by less frequent network reconfigurations while those who did not change their opinions tend to have more flexible brain networks with frequent reconfigurations. The nature of these frequent network configurations suggests a fundamentally different thought process between intervals in which individuals are easily influenced by social media and those in which they are not. We also show that these reconfigurations are distinct to the brain dynamics during an in-person discussion with strangers on the same content. Together, these findings suggest that brain network reconfigurations may not only be diagnostic to the informational context but also the underlying opinion formation.

Preserved capacity for learning statistical regularities and directing selective attention after hippocampal lesions.

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.

Dissociating the impact of attention and expectation on early sensory processing.

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.

Cortical chimera states predict epileptic seizures.

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.

Preserved capacity for scene construction and shifts in perspective after hippocampal lesions.

The hippocampus has long been recognized as important for the formation of long-term memory. Recent work has suggested that the hippocampus might also be important for certain kinds of spatial operations, as in constructing scenes, shifting perspective, or perceiving the geometry of scenes and their boundaries. We explored this proposal using a task similar to one used previously that related hippocampal activity to scenes and their boundaries. In our study, participants viewed scenes from above that displayed walls and towers. After viewing each scene, participants saw a scene from ground level and judged whether it was the same as or different from the scene just presented. The number of towers and walls in each scene was manipulated so that it was possible to assess how the structure of the scene affected performance. Patients with hippocampal lesions performed similarly to controls in all task conditions and had no special difficulty as a function of the layout of a scene and its boundaries. In contrast, a patient with large medial temporal lobe (MTL) lesions was impaired. Taken together, our findings suggest that the hippocampus is not needed for scene construction, shifts in perspective, or perceiving the geometry of scenes. The impairment associated with large MTL lesions may result from damage in or near parahippocampal cortex.

Expectations Do Not Alter Early Sensory Processing during Perceptual Decision-Making.

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.

Changing the spatial scope of attention alters patterns of neural gain in human cortex.

Over the last several decades, spatial attention has been shown to influence the activity of neurons in visual cortex in various ways. These conflicting observations have inspired competing models to account for the influence of attention on perception and behavior. Here, we used electroencephalography (EEG) to assess steady-state visual evoked potentials (SSVEP) in human subjects and showed that highly focused spatial attention primarily enhanced neural responses to high-contrast stimuli (response gain), whereas distributed attention primarily enhanced responses to medium-contrast stimuli (contrast gain). Together, these data suggest that different patterns of neural modulation do not reflect fundamentally different neural mechanisms, but instead reflect changes in the spatial extent of attention.