Auditory Attention Activates Peripheral Visual Cortex

Background

Recent neuroimaging studies have revealed that putatively unimodal regions of visual cortex can be activated during auditory tasks in sighted as well as in blind subjects. However, the task determinants and functional significance of auditory occipital activations (AOAs) remains unclear.

Methodology/Principal Findings

We examined AOAs in an intermodal selective attention task to distinguish whether they were stimulus-bound or recruited by higher-level cognitive operations associated with auditory attention. Cortical surface mapping showed that auditory occipital activations were localized to retinotopic visual cortex subserving the far peripheral visual field. AOAs depended strictly on the sustained engagement of auditory attention and were enhanced in more difficult listening conditions. In contrast, unattended sounds produced no AOAs regardless of their intensity, spatial location, or frequency.

Conclusions/Significance

Auditory attention, but not passive exposure to sounds, routinely activated peripheral regions of visual cortex when subjects attended to sound sources outside the visual field. Functional connections between auditory cortex and visual cortex subserving the peripheral visual field appear to underlie the generation of AOAs, which may reflect the priming of visual regions to process soon-to-appear objects associated with unseen sound sources.     

A Model of Temporal Encoding of Stimulus Orientation by Neuronal Responses in the Primary Visual Cortex

It has been shown experimentally that the stimulus orientation that elicits the optimal response in an orientation column in the primary visual cortex (area V1) undergoes rapid systemic changes that last 10–100 ms. These changes allow different orientation columns to encode information from multiple items in the visual space (the so-called temporal encoding). However, the mechanism of these changes is still unknown. In addition, most of the modern biophysical models are unable to reproduce these changes; the peak orientation of their responses is constant over time. In this paper, we suggest a method to improve the firing-rate ring model of the orientation hypercolumn by replacing the spatial symmetric distribution of local connections with a spatial anti-symmetric distribution. As a result, we obtained a more perfect model that is capable of reproducing such changes. Moreover, their amplitude is proportional to the extent of asymmetry in the spatial distribution of local connections.     

Encoding Stimulus Information by Spike Numbers and Mean Response Time in Primary Auditory Cortex

Neurons can transmit information about sensory stimuli via their firing rate, spike latency, or by the occurrence of complex spike patterns. Identifying which aspects of the neural responses actually encode sensory information remains a fundamental question in neuroscience. Here we compared various approaches for estimating the information transmitted by neurons in auditory cortex in two very different experimental paradigms, one measuring spatial tuning and the other responses to complex natural stimuli. We demonstrate that, in both cases, spike counts and mean response times jointly carry essentially all the available information about the stimuli. Thus, in auditory cortex, whereas spike counts carry only partial information about stimulus identity or location, the additional availability of relatively coarse temporal information is sufficient in order to extract essentially all the sensory information available in the spike discharge pattern, at least for the relatively short stimuli (< ∼ 100 ms) commonly used in auditory research.     

Distributed Fading Memory for Stimulus Properties in the Primary Visual Cortex

It is currently not known how distributed neuronal responses in early visual areas carry stimulus-related information. We made multielectrode recordings from cat primary visual cortex and applied methods from machine learning in order to analyze the temporal evolution of stimulus-related information in the spiking activity of large ensembles of around 100 neurons. We used sequences of up to three different visual stimuli (letters of the alphabet) presented for 100 ms and with intervals of 100 ms or larger. Most of the information about visual stimuli extractable by sophisticated methods of machine learning, i.e., support vector machines with nonlinear kernel functions, was also extractable by simple linear classification such as can be achieved by individual neurons. New stimuli did not erase information about previous stimuli. The responses to the most recent stimulus contained about equal amounts of information about both this and the preceding stimulus. This information was encoded both in the discharge rates (response amplitudes) of the ensemble of neurons and, when using short time constants for integration (e.g., 20 ms), in the precise timing of individual spikes (≤∼20 ms), and persisted for several 100 ms beyond the offset of stimuli. The results indicate that the network from which we recorded is endowed with fading memory and is capable of performing online computations utilizing information about temporally sequential stimuli. This result challenges models assuming frame-by-frame analyses of sequential inputs.     

How the Visual Cortex Handles Stimulus Noise: Insights from Amblyopia

Adding noise to a visual image makes object recognition more effortful and has a widespread effect on human electrophysiological responses. However, visual cortical processes directly involved in handling the stimulus noise have yet to be identified and dissociated from the modulation of the neural responses due to the deteriorated structural information and increased stimulus uncertainty in the case of noisy images. Here we show that the impairment of face gender categorization performance in the case of noisy images in amblyopic patients correlates with amblyopic deficits measured in the noise-induced modulation of the P1/P2 components of single-trial event-related potentials (ERP). On the other hand, the N170 ERP component is similarly affected by the presence of noise in the two eyes and its modulation does not predict the behavioral deficit. These results have revealed that the efficient processing of noisy images depends on the engagement of additional processing resources both at the early, feature-specific as well as later, object-level stages of visual cortical processing reflected in the P1 and P2 ERP components, respectively. Our findings also suggest that noise-induced modulation of the N170 component might reflect diminished face-selective neuronal responses to face images with deteriorated structural information.     

Auditory Evoked Bursts in Mouse Visual Cortex during Isoflurane Anesthesia

General anesthesia is not a uniform state of the brain. Ongoing activity differs between light and deep anesthesia and cortical response properties are modulated in dependence of anesthetic dosage. We investigated how anesthesia level affects cross-modal interactions in primary sensory cortex. To examine this, we continuously measured the effects of visual and auditory stimulation during increasing and decreasing isoflurane level in the mouse visual cortex and the subiculum (from baseline at 0.7 to 2.5 vol % and reverse). Auditory evoked burst activity occurred in visual cortex after a transition during increase of anesthesia level. At the same time, auditory and visual evoked bursts occurred in the subiculum, even though the subiculum was unresponsive to both stimuli previous to the transition. This altered sensory excitability was linked to the presence of burst suppression activity in cortex, and to a regular slow burst suppression rhythm (∼0.2 Hz) in the subiculum. The effect disappeared during return to light anesthesia. The results show that pseudo-heteromodal sensory burst responses can appear in brain structures as an effect of an anesthesia induced state change.     

Integration of Visual Information in Auditory Cortex Promotes Auditory Scene Analysis through Multisensory Binding

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视皮层神经元活动的振荡和同步振荡现象

视皮层神经元电活动的振荡和同步振荡现象是神经生理学实验的最新发现之一.这一研究成果在认知科学界引起广泛关注.学术界对它在认知心理学上的解释、作用及意义有不同的评论.     

Stimulus Phase Locking of Cortical Oscillation for Auditory Stream Segregation in Rats

The phase of cortical oscillations contains rich information and is valuable for encoding sound stimuli. Here we hypothesized that oscillatory phase modulation, instead of amplitude modulation, is a neural correlate of auditory streaming. Our behavioral evaluation provided compelling evidences for the first time that rats are able to organize auditory stream. Local field potentials (LFPs) were investigated in the cortical layer IV or deeper in the primary auditory cortex of anesthetized rats. In response to ABA- sequences with different inter-tone intervals and frequency differences, neurometric functions were characterized with phase locking as well as the band-specific amplitude evoked by test tones. Our results demonstrated that under large frequency differences and short inter-tone intervals, the neurometric function based on stimulus phase locking in higher frequency bands, particularly the gamma band, could better describe van Noorden’s perceptual boundary than the LFP amplitude. Furthermore, the gamma-band neurometric function showed a build-up-like effect within around 3 seconds from sequence onset. These findings suggest that phase locking and amplitude have different roles in neural computation, and support our hypothesis that temporal modulation of cortical oscillations should be considered to be neurophysiological mechanisms of auditory streaming, in addition to forward suppression, tonotopic separation, and multi-second adaptation.     

Functionally Distinct Gamma Range Activity Revealed by Stimulus Tuning in Human Visual Cortex

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Dynamics of Vocalization-Induced Modulation of Auditory Cortical Activity at Mid-utterance

Background

Recent research has addressed the suppression of cortical sensory responses to altered auditory feedback that occurs at utterance onset regarding speech. However, there is reason to assume that the mechanisms underlying sensorimotor processing at mid-utterance are different than those involved in sensorimotor control at utterance onset. The present study attempted to examine the dynamics of event-related potentials (ERPs) to different acoustic versions of auditory feedback at mid-utterance.

Methodology/Principal findings

Subjects produced a vowel sound while hearing their pitch-shifted voice (100 cents), a sum of their vocalization and pure tones, or a sum of their vocalization and white noise at mid-utterance via headphones. Subjects also passively listened to playback of what they heard during active vocalization. Cortical ERPs were recorded in response to different acoustic versions of feedback changes during both active vocalization and passive listening. The results showed that, relative to passive listening, active vocalization yielded enhanced P2 responses to the 100 cents pitch shifts, whereas suppression effects of P2 responses were observed when voice auditory feedback was distorted by pure tones or white noise.

Conclusion/Significance

The present findings, for the first time, demonstrate a dynamic modulation of cortical activity as a function of the quality of acoustic feedback at mid-utterance, suggesting that auditory cortical responses can be enhanced or suppressed to distinguish self-produced speech from externally-produced sounds.     

Dissociable Neural Response Signatures for Slow Amplitude and Frequency Modulation in Human Auditory Cortex

Natural auditory stimuli are characterized by slow fluctuations in amplitude and frequency. However, the degree to which the neural responses to slow amplitude modulation (AM) and frequency modulation (FM) are capable of conveying independent time-varying information, particularly with respect to speech communication, is unclear. In the current electroencephalography (EEG) study, participants listened to amplitude- and frequency-modulated narrow-band noises with a 3-Hz modulation rate, and the resulting neural responses were compared. Spectral analyses revealed similar spectral amplitude peaks for AM and FM at the stimulation frequency (3 Hz), but amplitude at the second harmonic frequency (6 Hz) was much higher for FM than for AM. Moreover, the phase delay of neural responses with respect to the full-band stimulus envelope was shorter for FM than for AM. Finally, the critical analysis involved classification of single trials as being in response to either AM or FM based on either phase or amplitude information. Time-varying phase, but not amplitude, was sufficient to accurately classify AM and FM stimuli based on single-trial neural responses. Taken together, the current results support the dissociable nature of cortical signatures of slow AM and FM. These cortical signatures potentially provide an efficient means to dissect simultaneously communicated slow temporal and spectral information in acoustic communication signals.     

初级视皮层神经元集群对拓扑特征响应的可视化表征

神经元集群响应的高维特性是脑机制研究面临的主要困难之一.拓扑特征是图像的基本特征之一,为了有效表征高维的神经元集群响应的拓扑特征特性,提出了一种基于三维自组织映射网络采用RGB颜色特征表征神经元集群响应的动态可视化方法,分析多通道微电极阵列采集的大鼠初级视觉皮层(V1区)神经元集群信号,进而研究了V1区神经元集群对图形拓扑特征的响应特性.通过与主成分分析(PCA)方法进行对比发现:该方法能够有效表征V1区神经元集群对拓扑结构的时序动态响应特征,表征方式形象直观,具有一定的优越性.