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OBJECTIVES/SPECIFIC AIMS: Attention is a cognitive function that binds perception and behavior. Recent evidence suggests that attention involves phase-amplitude coupling (PAC) of neural signals. PAC occurs when the amplitude of one frequency (frequency for amplitude) is maximal at particular phases of another frequency (frequency for phase). However, some studies suggest PAC improves attention, while others maintain that PAC inhibits attention. The present study seeks to determine whether PAC promotes or inhibits neural signals that underlie attention. METHODS/STUDY POPULATION: Six adult epilepsy patients with implanted electrodes participated in a cued attention task. Subjects participated in a cued attention task where they oriented attention to one side of the screen at a time and discriminated between stimuli as fast as possible with mouse clicks. Perception-related electrodes discriminated the location and/or shape of the target. These were determined with a cluster-based permutation test. Behavior-related electrodes predicted reaction time (RT) with neural activity prior to target appearance. These were determined with correlations between PAC and RT. PAC was calculated using the modulation index (MI). RESULTS/ANTICIPATED RESULTS: We found 47 perception-related electrodes that discriminated location and/or shape of target (p<0.05, FDR corrected). We found 27 behavior-related electrodes where PAC prior to the target predicted RT (p<0.05 FDR corrected). There was little overlap between the perception-related and behavior-related electrodes (3%). PAC also did not discriminate left-sided and right-sided cues. In addition, behavior-related electrodes had less local neural activity and higher PAC during the period of cued attention than perception-related electrodes. DISCUSSION/SIGNIFICANCE OF IMPACT: PAC minimally facilitates perceptual aspect of visual attention. However, PAC facilitate response speed. We suggest that PAC might improve response speed by “quieting” task irrelevant neural activity. For the same reason, PAC is absent in electrodes that are actively processing meaningful streams of visual data. These findings highlight separable aspects of the human attention system and how PAC contributes to both. Future directions include determining differences in PAC for attentional disorders like ADHD and neurological neglect.

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Interpersonal Comparison of Utility by Measuring Neural Activity

10.1101/2021.06.04.447048 ◽

2021 ◽

Author(s):

Kaosu Matsumori ◽

Kazuki Iijima ◽

Yukihito Yomogida ◽

Kenji Matsumoto

Keyword(s):

Neural Activity ◽

Optimal Taxation ◽

Cost Benefit ◽

Third Party ◽

Impossibility Theorem ◽

Interpersonal Comparison ◽

Neural Signals ◽

Collective Decisions ◽

Economic Goods ◽

Household Incomes

Aggregating welfare across individuals to reach collective decisions is one of the most fundamental problems in our society. Interpersonal comparison of utility is pivotal and inevitable for welfare aggregation, because if each person's utility is not interpersonally comparable, there is no rational aggregation procedure that simultaneously satisfies even some very mild conditions for validity (Arrow's impossibility theorem). However, scientific methods for interpersonal comparison of utility have thus far not been available. Here, we have developed a method for interpersonal comparison of utility based on brain signals, by measuring the neural activity of participants performing gambling tasks. We found that activity in the medial frontal region was correlated with changes in expected utility, and that, for the same amount of money, the activity evoked was larger for participants with lower household incomes than for those with higher household incomes. Furthermore, we found that the ratio of neural signals from lower-income participants to those of higher-income participants coincided with estimates of their psychological pleasure by "impartial spectators", i.e. disinterested third-party participants satisfying specific conditions. Finally, we derived a decision rule based on aggregated welfare from our experimental data, and confirmed that it was applicable to a distribution problem. These findings suggest that our proposed method for interpersonal comparison of utility enables scientifically reasonable welfare aggregation by escaping from Arrow's impossibility and has implications for the fair distribution of economic goods. Our method can be further applied for evidence-based policy making in nations that use cost-benefit analyses or optimal taxation theory for policy evaluation.

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Dissecting the Neural Focus of Attention Reveals Distinct Processes for Spatial Attention and Object-Based Storage in Visual Working Memory

Psychological Science ◽

10.1177/0956797619830384 ◽

2019 ◽

Vol 30 (4) ◽

pp. 526-540 ◽

Cited By ~ 27

Author(s):

Nicole Hakim ◽

Kirsten C. S. Adam ◽

Eren Gunseli ◽

Edward Awh ◽

Edward K. Vogel

Keyword(s):

Working Memory ◽

Spatial Attention ◽

Spatial Information ◽

Focus Of Attention ◽

Neural Signals ◽

Attention Task ◽

Spatial Orienting ◽

Object Based ◽

Object Storage ◽

On Line

Complex cognition relies on both on-line representations in working memory (WM), said to reside in the focus of attention, and passive off-line representations of related information. Here, we dissected the focus of attention by showing that distinct neural signals index the on-line storage of objects and sustained spatial attention. We recorded electroencephalogram (EEG) activity during two tasks that employed identical stimulus displays but varied the relative demands for object storage and spatial attention. We found distinct delay-period signatures for an attention task (which required only spatial attention) and a WM task (which invoked both spatial attention and object storage). Although both tasks required active maintenance of spatial information, only the WM task elicited robust contralateral delay activity that was sensitive to mnemonic load. Thus, we argue that the focus of attention is maintained via a collaboration between distinct processes for covert spatial orienting and object-based storage.

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Why the Assessment of Causality in Brain–Behavior Relations Requires Brain Stimulation

Journal of Cognitive Neuroscience ◽

10.1162/jocn_a_00193 ◽

2012 ◽

Vol 24 (4) ◽

pp. 775-777 ◽

Cited By ~ 24

Author(s):

Juha Silvanto ◽

Alvaro Pascual-Leone

Keyword(s):

Opposite Direction ◽

Brain Stimulation ◽

Cognitive Neuroscience ◽

Neural Activity ◽

Functional Neuroimaging ◽

Brain Activity ◽

Causal Link ◽

And Behavior ◽

Brain Behavior

A central aim in cognitive neuroscience is to explain how neural activity gives rise to perception and behavior; the causal link of paramount interest is thus from brain to behavior. Functional neuroimaging studies, however, tend to provide information in the opposite direction by informing us how manipulation of behavior may affect neural activity. Although this may provide valuable insights into neuronal properties, one cannot use such evidence to make inferences about the behavioral significance of the observed activations; if A causes B, it does not necessarily follow that B causes A. In contrast, brain stimulation techniques enable us to directly modulate brain activity as the source of behavior and thus establish causal links.

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Rapid Association Learning in the Primate Prefrontal Cortex in the Absence of Behavioral Reversals

Journal of Cognitive Neuroscience ◽

10.1162/jocn.2010.21555 ◽

2011 ◽

Vol 23 (7) ◽

pp. 1823-1828 ◽

Cited By ~ 11

Author(s):

Jason A. Cromer ◽

Michelle Machon ◽

Earl K. Miller

Keyword(s):

Prefrontal Cortex ◽

Neural Activity ◽

Association Learning ◽

Conditional Association ◽

And Behavior ◽

The Relationship ◽

Behavioral Improvement ◽

Previous Learning

The PFC plays a central role in our ability to learn arbitrary rules, such as “green means go.” Previous experiments from our laboratory have used conditional association learning to show that slow, gradual changes in PFC neural activity mirror monkeys' slow acquisition of associations. These previous experiments required monkeys to repeatedly reverse the cue–saccade associations, an ability known to be PFC-dependent. We aimed to test whether the relationship between PFC neural activity and behavior was due to the reversal requirement, so monkeys were trained to learn several new conditional cue–saccade associations without reversing them. Learning-related changes in PFC activity now appeared earlier and more suddenly in correspondence with similar changes in behavioral improvement. This suggests that learning of conditional associations is linked to PFC activity regardless of whether reversals are required. However, when previous learning does not need to be suppressed, PFC acquires associations more rapidly.

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Dynamic Coding of Events within the Inferior Frontal Gyrus in a Probabilistic Selective Attention Task

Journal of Cognitive Neuroscience ◽

10.1162/jocn.2010.21441 ◽

2011 ◽

Vol 23 (2) ◽

pp. 414-424 ◽

Cited By ~ 16

Author(s):

Simone Vossel ◽

Ralph Weidner ◽

Gereon R. Fink

Keyword(s):

Neural Activity ◽

Inferior Frontal Gyrus ◽

Preceding Trial ◽

Behavioral Effect ◽

Spatial Cues ◽

Attention Task ◽

Fmri Study ◽

Sequence Effects ◽

Parametric Effects ◽

The Right

Besides the fact that RTs in cognitive tasks are affected by the specific demands of a trial, the context in which this trial occurs codetermines the speed of the response. For instance, invalid spatial cues generally prolong RTs to targets in the location-cueing paradigm, whereas the magnitude of these RT costs additionally varies as a function of the preceding trial types so that RTs for invalid trials may be increased when preceded by valid rather than invalid trials. In the present fMRI study, we investigated trial sequence effects in a combined oddball and location-cueing paradigm. In particular, we tested whether RTs and neural activity to infrequent invalid or deviant targets varied as a function of the number of preceding valid standard trials. As expected, RTs in invalid and deviant trials were significantly slower when more valid standard trials had been presented beforehand. This behavioral effect was reflected in the neural activity of the right inferior/middle frontal gyrus where the amplitude of the hemodynamic response in invalid and deviant trials was positively related to the number of preceding valid standard trials. In contrast, decreased activity (i.e., a negative parametric modulation effect) was observed when more valid standard trials were successively presented. Further positive parametric effects for the number of preceding valid standard trials were observed in the left caudate nucleus and lingual gyrus. The data suggest that inferior frontal cortex extracts both event regularities and irregularities in event streams.

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Graphene-Based Electrode Materials for Neural Activity Detection

Materials ◽

10.3390/ma14206170 ◽

2021 ◽

Vol 14 (20) ◽

pp. 6170

Author(s):

Weichen Wei ◽

Xuejiao Wang

Keyword(s):

Neural Activity ◽

High Performance ◽

Electrode Materials ◽

Neurological Diseases ◽

Activity Detection ◽

Neural Signals ◽

Neural Electrode ◽

Neural Electrodes ◽

Wide Range

The neural electrode technique is a powerful tool for monitoring and regulating neural activity, which has a wide range of applications in basic neuroscience and the treatment of neurological diseases. Constructing a high-performance electrode–nerve interface is required for the long-term stable detection of neural signals by electrodes. However, conventional neural electrodes are mainly fabricated from rigid materials that do not match the mechanical properties of soft neural tissues, thus limiting the high-quality recording of neuroelectric signals. Meanwhile, graphene-based nanomaterials can form stable electrode–nerve interfaces due to their high conductivity, excellent flexibility, and biocompatibility. In this literature review, we describe various graphene-based electrodes and their potential application in neural activity detection. We also discuss the biological safety of graphene neural electrodes, related challenges, and their prospects.

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Integration of locomotion and auditory signals in the mouse inferior colliculus

10.1101/795872 ◽

2019 ◽

Author(s):

Yoonsun Yang ◽

Joonyeol Lee ◽

Gunsoo Kim

Keyword(s):

Inferior Colliculus ◽

Neural Activity ◽

Stimulus Presentation ◽

Sound Stimulus ◽

Frequency Selectivity ◽

Auditory Information ◽

Neural Signals ◽

Sound Processing ◽

Auditory Integration ◽

Evoked Activity

AbstractThe inferior colliculus (IC) is the major midbrain auditory integration center, where virtually all ascending auditory inputs converge. Although the IC has been extensively studied for sound processing, little is known about the neural activity of the IC in moving subjects, as frequently happens in natural hearing conditions. Here we show, by recording the IC neural activity in walking mice, the activity of IC neurons is strongly modulated by locomotion in the absence of sound stimulus presentation. Similar modulation was also found in deafened mice, demonstrating that IC neurons receive non-auditory, locomotion-related neural signals. Sound-evoked activity was attenuated during locomotion, and the attenuation increased frequency selectivity across the population, while maintaining preferred frequencies. Our results suggest that during behavior, integrating movement-related and auditory information is an essential aspect of sound processing in the IC.

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Exploratory methods for high-performance EEG speech decoding

10.1101/2021.11.16.468876 ◽

2021 ◽

Author(s):

Lindy B Comstock ◽

Claudia Lainscsek ◽

Vinícius Rezende Carvalho ◽

Eduardo Mendes ◽

Aria Fallah ◽

...

Keyword(s):

Nonlinear Dynamics ◽

High Performance ◽

Signal To Noise Ratio ◽

Computational Method ◽

Differential Analysis ◽

Neural Signals ◽

Widespread Application ◽

Implanted Electrodes ◽

Viable Solution ◽

Delay Differential

State-of-the-art technologies in neural speech decoding utilize data collected from microwires or microarrays implanted directly into the cerebral cortex. Yet as a tool accessible only to individuals with implanted electrodes, speech decoding from devices of this nature is severely limited in its implementation, and cannot be considered a viable solution for widespread application. Speech decoding from non-invasive EEG signals can achieve relatively high accuracy (70-80\%), but only from very small classification tasks, with more complex tasks typically yielding a limited (20-50\%) classification accuracy. We propose a novel combination of technologies in which transcranial magnetic stimulation (TMS) is first applied to augment the neural signals of interest, producing a greater signal-to-noise ratio in the EEG data. Next, delay differential analysis (DDA) -- a cutting-edge computational method based on nonlinear dynamics -- is implemented to capture the widest range of information available in the neural signal, by incorporating both linear and nonlinear dynamics.

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