scholarly journals Responses of Auditory Cortex to Complex Stimuli: Functional Organization Revealed Using Intrinsic Optical Signals

2008 ◽  
Vol 99 (4) ◽  
pp. 1928-1941 ◽  
Author(s):  
Israel Nelken ◽  
Jennifer K. Bizley ◽  
Fernando R. Nodal ◽  
Bashir Ahmed ◽  
Andrew J. King ◽  
...  
Keyword(s):  
Auditory Cortex ◽  
Optical Imaging ◽  
Large Scale ◽  
Functional Organization ◽  
Broadband Noise ◽  
Spectral Structure ◽  
Imaging Data ◽  
Complex Sounds ◽  
Optical Signals ◽  
Interaural Level Differences

We used optical imaging of intrinsic signals to study the large-scale organization of ferret auditory cortex in response to complex sounds. Cortical responses were collected during continuous stimulation by sequences of sounds with varying frequency, period, or interaural level differences. We used a set of stimuli that differ in spectral structure, but have the same periodicity and therefore evoke the same pitch percept (click trains, sinusoidally amplitude modulated tones, and iterated ripple noise). These stimuli failed to reveal a consistent periodotopic map across the auditory fields imaged. Rather, gradients of period sensitivity differed for the different types of periodic stimuli. Binaural interactions were studied both with single contralateral, ipsilateral, and diotic broadband noise bursts and with sequences of broadband noise bursts with varying level presented contralaterally, ipsilaterally, or in opposite phase to both ears. Contralateral responses were generally largest and ipsilateral responses were smallest when using single noise bursts, but the extent of the activated area was large and comparable in all three aural configurations. Modulating the amplitude in counter phase to the two ears generally produced weaker modulation of the optical signals than the modulation produced by the monaural stimuli. These results suggest that binaural interactions seen in cortex are most likely predominantly due to subcortical processing. Thus our optical imaging data do not support the theory that the primary or nonprimary cortical fields imaged are topographically organized to form consistent maps of systematically varying sensitivity either to stimulus pitch or to simple binaural properties of the acoustic stimuli.

scholarly journals A novel dynamic network imaging analysis method reveals aging-related fragmentation of cortical networks in mouse

2019 ◽  
Author(s):  
Daniel A Llano ◽  
Chihua Ma ◽  
Umberto Di Fabrizio ◽  
Aynaz Taheri ◽  
Kevin A. Stebbings ◽  
...  
Keyword(s):  
Auditory Cortex ◽  
Large Scale ◽  
Brain Slices ◽  
Dynamic Network ◽  
Analytical Tool ◽  
Aging Brain ◽  
Autofluorescence Imaging ◽  
Imaging Data ◽  
Cortical Networks ◽  
Network Metrics

AbstractNetwork analysis of large-scale neuroimaging data has proven to be a particularly challenging computational problem. In this study, we adapt a novel analytical tool, known as the community dynamic inference method (CommDy), which was inspired by social network theory, for the study of brain imaging data from an aging mouse model. CommDy has been successfully used in other domains in biology; this report represents its first use in neuroscience. We used CommDy to investigate aging-related changes in network parameters in the auditory and motor cortices using flavoprotein autofluorescence imaging in brain slices and in vivo. Analysis of spontaneous activations in the auditory cortex of slices taken from young and aged animals demonstrated that cortical networks in aged brains were highly fragmented compared to networks observed in young animals. Specifically, the degree of connectivity of each activated node in the aged brains was significantly lower than those seen in the young brain, and multivariate analyses of all derived network metrics showed distinct clusters of these metrics in young vs. aged brains. CommDy network metrics were then used to build a random-forests classifier based on NMDA-receptor blockade data, which successfully recapitulated the aging findings, suggesting that the excitatory synaptic substructure of the auditory cortex may be altered during aging. A similar aging-related decline in network connectivity was also observed in spontaneous activity obtained from the awake motor cortex, suggesting that the findings in the auditory cortex are reflections of general mechanisms that occur during aging. Therefore, CommDy therefore provides a new dynamic network analytical tool to study the brain and provides links between network-level and synaptic-level dysfunction in the aging brain.

scholarly journals A Late Critical Period for Frequency Modulated Sweeps in the Mouse Auditory System

2019 ◽  
Vol 30 (4) ◽  
pp. 2586-2599 ◽  
Author(s):  
Stitipragyan Bhumika ◽  
Mari Nakamura ◽  
Patricia Valerio ◽  
Magdalena Solyga ◽  
Henrik Lindén ◽  
...  
Keyword(s):  
Auditory Cortex ◽  
Auditory System ◽  
Critical Period ◽  
Noise Exposure ◽  
Functional Organization ◽  
Time Windows ◽  
Immunohistochemical Analysis ◽  
Critical Periods ◽  
Complex Sounds

Abstract Neuronal circuits are shaped by experience during time windows of increased plasticity in postnatal development. In the auditory system, the critical period for the simplest sounds—pure frequency tones—is well defined. Critical periods for more complex sounds remain to be elucidated. We used in vivo electrophysiological recordings in the mouse auditory cortex to demonstrate that passive exposure to frequency modulated sweeps (FMS) from postnatal day 31 to 38 leads to long-term changes in the temporal representation of sweep directions. Immunohistochemical analysis revealed a decreased percentage of layer 4 parvalbumin-positive (PV+) cells during this critical period, paralleled with a transient increase in responses to FMS, but not to pure tones. Preventing the PV+ cell decrease with continuous white noise exposure delayed the critical period onset, suggesting a reduction in inhibition as a mechanism for this plasticity. Our findings shed new light on the dependence of plastic windows on stimulus complexity that persistently sculpt the functional organization of the auditory cortex.

scholarly journals Fine functional organization of auditory cortex revealed by Fourier optical imaging

2005 ◽  
Vol 102 (37) ◽  
pp. 13325-13330 ◽  
Author(s):  
V. A. Kalatsky ◽  
D. B. Polley ◽  
M. M. Merzenich ◽  
C. E. Schreiner ◽  
M. P. Stryker
Keyword(s):  
Auditory Cortex ◽  
Optical Imaging ◽  
Functional Organization

Functional Organization of the Pallid Bat Auditory Cortex: Emphasis on Binaural Organization

2002 ◽  
Vol 87 (1) ◽  
pp. 72-86 ◽  
Author(s):  
Khaleel A. Razak ◽  
Zoltan M. Fuzessery
Keyword(s):  
Auditory Cortex ◽  
Sound Localization ◽  
High Frequency ◽  
Functional Organization ◽  
Low Frequency ◽  
Frequency Region ◽  
Broadband Noise ◽  
Intensity Difference ◽  
Band Pass ◽  
Pallid Bat

This report maps the organization of the primary auditory cortex of the pallid bat in terms of frequency tuning, selectivity for behaviorally relevant sounds, and interaural intensity difference (IID) sensitivity. The pallid bat is unusual in that it localizes terrestrial prey by passively listening to prey-generated noise transients (1–20 kHz), while reserving high-frequency (<30 kHz) echolocation for obstacle avoidance. The functional organization of its auditory cortex reflects the need for specializations in echolocation and passive sound localization. Best frequencies were arranged tonotopically with a general increase in the caudolateral to rostromedial direction. Frequencies between 24 and 32 kHz were under-represented, resulting in hypertrophy of frequencies relevant for prey localization and echolocation. Most neurons (83%) tuned <30 kHz responded preferentially to broadband or band-pass noise over single tones. Most neurons (62%) tuned >30 kHz responded selectively or exclusively to the 60- to 30-kHz downward frequency-modulated (FM) sweep used for echolocation. Within the low-frequency region, neurons were placed in two groups that occurred in two separate clusters: those selective for low- or high-frequency band-pass noise and suppressed by broadband noise, and neurons that showed no preference for band-pass noise over broadband noise. Neurons were organized in homogeneous clusters with respect to their binaural response properties. The distribution of binaural properties differed in the noise- and FM sweep-preferring regions, suggesting task-dependent differences in binaural processing. The low-frequency region was dominated by a large cluster of binaurally inhibited neurons with a smaller cluster of neurons with mixed binaural interactions. The FM sweep-selective region was dominated by neurons with mixed binaural interactions or monaural neurons. Finally, this report describes a cortical substrate for systematic representation of a spatial cue, IIDs, in the low-frequency region. This substrate may underlie a population code for sound localization based on a systematic shift in the distribution of activity across the cortex with sound source location.

Effect of bilateral auditory cortex lesions on absolute thresholds in Japanese macaques

1990 ◽  
Vol 64 (1) ◽  
pp. 191-205 ◽  
Author(s):  
H. E. Heffner ◽  
R. S. Heffner
Keyword(s):  
Hearing Loss ◽  
Auditory Cortex ◽  
Sound Localization ◽  
Functional Organization ◽  
Japanese Macaques ◽  
Broadband Noise ◽  
Partial Recovery ◽  
Rapid Phase ◽  
Contralateral Ear ◽  
Bilateral Lesions

1. The behavioral audiograms of four Japanese macaques (Macaca fuscata) were assessed before and after receiving two-stage bilateral lesions of auditory cortex. Thresholds were assessed for each ear with the use of insertion earphones. 2. The bilateral lesions resulted in a large initial hearing loss followed by partial recovery that left the animals with a permanent hearing loss in both ears. 3. The initial hearing loss consisted of a total insensitivity to sound in the ear contralateral to the second lesion with limited hearing in the other ear. However, the animal with the most complete lesion was initially unable to hear sound in either ear. Broadband noise was often more effective in eliciting a behavioral response than tones. 4. Partial recovery occurred in all animals and was observed as early as the first week after surgery. Most of this recovery occurred during the first 3-7 wk after surgery. This rapid phase of recovery was sometimes followed by a more gradual phase although thresholds were still elevated after 94 wk. 5. The permanent hearing loss, which averaged from 30 to 44 dB, was not constant across frequency. Threshold shifts were smallest at 63 Hz and progressively increased with frequency to a maximum loss from 8 to 25 kHz with slightly less loss at 32 kHz. 6. Analysis of the psychophysical functions and threshold stability gave no indication of any nonsensory deficits in attention or vigilance. 7. These results, taken with those of previous experiments, indicate that each hemisphere is primarily involved in the detection of sound in the contralateral ear and secondarily involved in detection in the ipsilateral ear. This arrangement differs from that seen in sound localization where each hemisphere is involved with the contralateral hemifield as opposed to the contralateral ear. Thus it appears that the functional organization of auditory cortex for sound localization is different from that for the detection and identification of sound itself.

scholarly journals Fractional ridge regression: a fast, interpretable reparameterization of ridge regression

GigaScience ◽  
2020 ◽  
Vol 9 (12) ◽  
Author(s):  
Ariel Rokem ◽  
Kendrick Kay
Keyword(s):  
Ridge Regression ◽  
Large Scale ◽  
Imaging Data ◽  
Regularization Technique ◽  
Large Scale Data ◽  
Novel Approach ◽  
Manual Exploration ◽  
L2 Norm ◽  
Software Implementations ◽  
Brain Imaging Data

Abstract Background Ridge regression is a regularization technique that penalizes the L2-norm of the coefficients in linear regression. One of the challenges of using ridge regression is the need to set a hyperparameter (α) that controls the amount of regularization. Cross-validation is typically used to select the best α from a set of candidates. However, efficient and appropriate selection of α can be challenging. This becomes prohibitive when large amounts of data are analyzed. Because the selected α depends on the scale of the data and correlations across predictors, it is also not straightforwardly interpretable. Results The present work addresses these challenges through a novel approach to ridge regression. We propose to reparameterize ridge regression in terms of the ratio γ between the L2-norms of the regularized and unregularized coefficients. We provide an algorithm that efficiently implements this approach, called fractional ridge regression, as well as open-source software implementations in Python and matlab (https://github.com/nrdg/fracridge). We show that the proposed method is fast and scalable for large-scale data problems. In brain imaging data, we demonstrate that this approach delivers results that are straightforward to interpret and compare across models and datasets. Conclusion Fractional ridge regression has several benefits: the solutions obtained for different γ are guaranteed to vary, guarding against wasted calculations; and automatically span the relevant range of regularization, avoiding the need for arduous manual exploration. These properties make fractional ridge regression particularly suitable for analysis of large complex datasets.

scholarly journals The unbalanced reorganization of weaker functional connections induces the altered brain network topology in schizophrenia

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Rossana Mastrandrea ◽  
Fabrizio Piras ◽  
Andrea Gabrielli ◽  
Nerisa Banaj ◽  
Guido Caldarelli ◽  
...  
Keyword(s):  
Resting State ◽  
Functional Organization ◽  
Functional Integration ◽  
Brain Network ◽  
Modular Organization ◽  
Node Degree ◽  
Imaging Data ◽  
Brain Disorder ◽  
Functional Connections ◽  
The Brain

AbstractNetwork neuroscience shed some light on the functional and structural modifications occurring to the brain associated with the phenomenology of schizophrenia. In particular, resting-state functional networks have helped our understanding of the illness by highlighting the global and local alterations within the cerebral organization. We investigated the robustness of the brain functional architecture in 44 medicated schizophrenic patients and 40 healthy comparators through an advanced network analysis of resting-state functional magnetic resonance imaging data. The networks in patients showed more resistance to disconnection than in healthy controls, with an evident discrepancy between the two groups in the node degree distribution computed along a percolation process. Despite a substantial similarity of the basal functional organization between the two groups, the expected hierarchy of healthy brains' modular organization is crumbled in schizophrenia, showing a peculiar arrangement of the functional connections, characterized by several topologically equivalent backbones. Thus, the manifold nature of the functional organization’s basal scheme, together with its altered hierarchical modularity, may be crucial in the pathogenesis of schizophrenia. This result fits the disconnection hypothesis that describes schizophrenia as a brain disorder characterized by an abnormal functional integration among brain regions.

Tonotopic representation of missing fundamental complex sounds in the human auditory cortex

2003 ◽  
Vol 18 (2) ◽  
pp. 432-440 ◽  
Author(s):  
Takako Fujioka ◽  
Bernhard Ross ◽  
Hidehiko Okamoto ◽  
Yasuyuki Takeshima ◽  
Ryusuke Kakigi ◽  
...  
Keyword(s):  
Auditory Cortex ◽  
Complex Sounds ◽  
Human Auditory Cortex ◽  
Missing Fundamental

Interferometric imaging condition for wave-equation migration

Geophysics ◽  
2008 ◽  
Vol 73 (2) ◽  
pp. S47-S61 ◽  
Author(s):  
Paul Sava ◽  
Oleg Poliannikov
Keyword(s):  
Large Scale ◽  
Wigner Distribution ◽  
Random Noise ◽  
Velocity Model ◽  
Distribution Functions ◽  
Small Scale ◽  
Interferometric Imaging ◽  
Imaging Data ◽  
Imaging Condition ◽  
Velocity Models

The fidelity of depth seismic imaging depends on the accuracy of the velocity models used for wavefield reconstruction. Models can be decomposed in two components, corresponding to large-scale and small-scale variations. In practice, the large-scale velocity model component can be estimated with high accuracy using repeated migration/tomography cycles, but the small-scale component cannot. When the earth has significant small-scale velocity components, wavefield reconstruction does not completely describe the recorded data, and migrated images are perturbed by artifacts. There are two possible ways to address this problem: (1) improve wavefield reconstruction by estimating more accurate velocity models and image using conventional techniques (e.g., wavefield crosscorrelation) or (2) reconstruct wavefields with conventional methods using the known background velocity model but improve the imaging condition to alleviate the artifacts caused by the imprecise reconstruction. Wedescribe the unknown component of the velocity model as a random function with local spatial correlations. Imaging data perturbed by such random variations is characterized by statistical instability, i.e., various wavefield components image at wrong locations that depend on the actual realization of the random model. Statistical stability can be achieved by preprocessing the reconstructed wavefields prior to the imaging condition. We use Wigner distribution functions to attenuate the random noise present in the reconstructed wavefields, parameterized as a function of image coordinates. Wavefield filtering using Wigner distribution functions and conventional imaging can be lumped together into a new form of imaging condition that we call an interferometric imaging condition because of its similarity to concepts from recent work on interferometry. The interferometric imaging condition can be formulated both for zero-offset and for multioffset data, leading to robust, efficient imaging procedures that effectively attenuate imaging artifacts caused by unknown velocity models.

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