Journal of Neuroscience最新文献

Our visual system can recognize patterns across many spatial scales. A fundamental assumption in visual neuroscience is that this ability relies on the putative scale-invariant properties of receptive fields (RFs) in early vision, whereby the spatial area over which a visual neuron responds is proportional to the spatial scale of information it can encode (i.e., spatial frequency, SF). In other words, the resolution of spatial sampling of a RF is assumed to be constant in the visual cortex. However, this assumption has gone untested in the human visual cortex. To address this, we leveraged model-based fMRI techniques that characterize the spatial tuning and SF preferences of cortical subpopulations sampled within a voxel across eight participants (five females, three males). We find that the voxel-wise ratio between peak SF tuning and RF size-expressed as "cycles per RF"-remains constant across visual areas V1, V2, and V3, suggesting that, at the population level, SF preferences are inversely proportional to the RF size, a tenet of scale invariance in early human vision.

Visuospatial attention is key for parsing visual information and selecting targets to look at. Based on regimented laboratory tasks, it is now well-established that three types of mechanism determine when and where attention is deployed; these are stimulus-driven (exogenous), goal-driven (endogenous), and history-driven (reflecting recent experience). It is unclear, however, how these distinct attentional signals interact and contribute in visual environments that are more akin to natural scanning, when stimuli may change rapidly and no fixation requirements are imposed. Here, we investigate this via a gamified task in which participants (male and female) make continuous saccadic choices at a rapid pace-and yet, perceptual performance can be accurately tracked over time as the choice process unfolds. The results reveal unequivocal markers of exogenous capture toward salient stimuli; endogenous guidance toward valuable targets and relevant locations; and history-driven effects, which produce large, involuntary modulations in processing capacity. Under dynamic conditions, success probability is dictated by temporally precise interplay between different forms of spatial attention, with recent history making a particularly prominent contribution.

Recent studies suggest some hippocampal (HC) neurons respond to passively presented sounds in naive subjects, but the specificity and prevalence of these responses remain unclear. We used Neuropixels probes to record unit activity across layers in mid-ventral HC and auditory cortex (ACtx) of awake, untrained mice (male and female) while presenting diverse sounds at typical environmental levels (65-70 dB SPL). A subset of HC neurons exhibited reliable, short latency responses to passive sounds, including tones and broadband noise. HC units showed evidence of tuning for tone frequency but not spectrotemporal features in continuous dynamic moving ripples. Across sound types, HC responses overwhelmingly occurred at stimulus onset; they quickly adapted to continuous sounds and did not respond at sound offset. Among all sounds tested, broadband noise was most effective at driving HC activity. Spectral manipulations indicated response prevalence scaled with increasing spectral bandwidth and density. Similar responses were also observed for visual flash and contrast-modulated noise movies, although these were less common than for broadband noise. Sound-evoked face movements, quantified by total face motion energy (FME), correlated with population-level HC activity. However, many individual units responded regardless of FME strength, suggesting both auditory and motor-correlated inputs. Together, our results show that abrupt sound onsets are sufficient to activate many HC neurons in the absence of learning or behavioral engagement. This supports a role for HC in detecting salient environmental changes and supports the idea that auditory inputs contribute directly to HC function.

Understanding how pupil-linked arousal couples with cortical state is crucial for uncovering the neural mechanisms underlying brain state-dependent cognitive and sensory processing. Pupil size fluctuations reflect rapid changes of the pupil-linked arousal system, indexing brain states as well as the activity of neuromodulatory systems, including the locus ceruleus-norepinephrine (LC-NE) system. We investigated the relationship among phasic pupil dilation, cortical state, and neuromodulation by combining optogenetic LC stimulation with electroencephalogram (EEG) recordings and pupillometry in awake mice of both sexes. A comparison between EEG signals during spontaneous phasic pupil dilation and those during phasic pupil dilation evoked by LC stimulation revealed distinct cortical states. Using machine learning techniques, we trained a convolutional neural network classifier to distinguish between types of pupil dilation based on the power dynamics of individual EEG frequency bands. The results confirmed that all EEG bands, but most significantly gamma, differ markedly between spontaneous phasic arousal and LC stimulation-evoked arousal. Moreover, pharmacological manipulations to either block α- or β-adrenergic receptors or agonize α-2-adrenergic receptors were employed to explore how adrenergic receptors could influence the coupling between phasic pupil dilation and cortical state. With each manipulation uniquely modulating EEG power and pupil size, our results highlight the differentiated role of adrenergic receptors in moderating the coupling between pupil-linked arousal and cortical state. This study provides new insights into the complex relationship between pupil-linked arousal and cortical arousal state, underscoring the significant role of the LC-NE system in influencing these arousal states.

Respiration has been shown to impact memory retrieval, yet the neural dynamics underlying this effect remain unclear. Here, we investigated how respiration shapes both behavioral and neural expressions of memory retrieval by reanalyzing an existing dataset where scalp electroencephalography and respiration recordings were acquired while participants (N = 18, 15 females) performed an episodic memory task. Our results unveil that respiration influences retrieval-related power fluctuations in the α/β band and concomitant memory reactivation. Specifically, we found that both key neural signatures of successful remembering were comodulated during exhalation, with the strength of the interaction between respiration and reactivation processes being associated with memory performance. Together, these findings suggest that respiration may act as a scaffold for episodic memory retrieval in humans by coordinating the neural conditions that support effective remembering.