ライフサイエンスコーパス: spectrotemporal

1 d stimuli of the other groups or to downward spectrotemporal (0.5 cyc/oct; -32 Hz) modulation.

2 Hz), temporal (0 cyc/oct; 32 Hz), or upward spectrotemporal (0.5 cyc/oct; 32 Hz) modulation.

3 uce no STRFs despite selective activation to spectrotemporal acoustic attributes.

4 ures could be directly related to tuning for spectrotemporal acoustic cues, some of which were encode

5 , we adopt a data-driven approach to map the spectrotemporal amplitude and functional connectivity (F

6 pond preferentially to linear or logarithmic spectrotemporal amplitudes.

7 ption of vertical or horizontal motion, with spectrotemporal analysis likely to be more important for

8 e application of warped stretch transform in spectrotemporal analysis of continuous-time signals.

9 hing the two ears (binaural cues) as well as spectrotemporal analysis of the waveform at each ear (mo

10 ta demonstrate two separate axes along which spectrotemporal aspects of sound are mapped: width of sp

11 reas in the auditory cortex use a dominantly spectrotemporal-based representation of the entire audit

12 as in the auditory cortex contain dominantly spectrotemporal-based representations of the entire audi

13 ed for three masker types differing in their spectrotemporal characteristics (noise, modulated noise,

14 By altering spectrotemporal characteristics of the masker, we reveal

15 revious studies using signals with differing spectrotemporal characteristics support a model in which

16 timuli, regardless of their elemental (i.e., spectrotemporal) characteristics.

17 figure and background that captures the rich spectrotemporal complexity of natural acoustic scenes.

18 ay have stronger harmonic content or greater spectrotemporal complexity.

19 These "courtship songs" differ in their spectrotemporal composition across species and are consi

20 his change in effective receptive field with spectrotemporal context improves predictions of both cor

21 One important property is the spectrotemporal contrast in the acoustic environment: th

22 STRFs of cortical neurons alongside a set of spectrotemporal contrast kernels.

23 e their gain to partially compensate for the spectrotemporal contrast of recent stimulation.

24 servation is intriguing for two reasons: (i) spectrotemporal dissociation in the auditory domain prov

25 to reconstruct the signal with low loss, the spectrotemporal distribution of the signal spectrum need

26 ns are sensitive over a substantially larger spectrotemporal domain than is seen in their standard sp

27 ed from these models to the spectral and the spectrotemporal domains and found that the spike initiat

28 eld energies and showed a net improvement in spectrotemporal encoding ability for logarithmic stimuli

29 cits may arise from defective interaction of spectrotemporal encoding and executive and mnestic proce

30 a broadband stimulus with a slowly modulated spectrotemporal envelope riding on top of a rapidly modu

31 A1 cells respond well to the slow spectrotemporal envelopes and produce a wide variety of

32 Just as STRFs measure the spectrotemporal features of a sound that lead to changes

33 of Mexican free-tailed bats encode multiple spectrotemporal features of natural communication sounds

34 This highly organized representation of spectrotemporal features of sound contrasts with current

35 ody (MGB), is increased when rapidly varying spectrotemporal features of speech sounds are processed,

36 ed, as compared to processing slowly varying spectrotemporal features of the same sounds.

37 M) echolocation sound sequences with dynamic spectrotemporal features served as acoustic stimuli alon

38 field characterization methods to show that spectrotemporal features within speech are well organize

39 alizations exhibit large variations in their spectrotemporal features, although it is still largely u

40 plasticity reflects increased sensitivity to spectrotemporal features, enhancing the extraction of mo

41 unctional classes on the basis of a suite of spectrotemporal features.

42 attended time points, in essence acting as a spectrotemporal filter mechanism.

43 Spectrotemporal information derived from such a 'computa

44 his work establishes an anatomical basis for spectrotemporal integration in the auditory midbrain and

45 Our findings delineate rules for spectrotemporal integration in the ICC that cannot be ac

46 ity in central auditory neurons is a form of spectrotemporal integration in which excitatory response

47 spiking dendrites increased and reduced the spectrotemporal integration window of the STA with incre

48 rying spectrum to study linear and nonlinear spectrotemporal interactions in the central nucleus of t

49 The nonlinear spectrotemporal maps derived from these neurons were cor

50 he possibility that a non-linguistic unaided spectrotemporal modulation (STM) detection test might be

51 measure of suprathreshold auditory function-spectrotemporal modulation (STM) sensitivity-and SRTs in

52 Here we examined the processing of spectrotemporal modulation behaviorally using a perceptu

53 ise was designed to match song in frequency, spectrotemporal modulation boundaries, and power.

54 rate robust functional organization based on spectrotemporal modulation content, and illustrate that

55 Here we characterized the spectrotemporal modulation statistics of several natural

56 modulation detection, but only when the same spectrotemporal modulation was used for both tasks.

57 zes sounds through filters tuned to combined spectrotemporal modulation.

58 This efficient use of logarithmic spectrotemporal modulations by auditory midbrain neurons

59 presentations in terms of frequency-specific spectrotemporal modulations enables accurate and specifi

60 relevant acoustic features and sounds (e.g., spectrotemporal modulations in the songs of zebra finche

61 ings and a stimulus that captures aspects of spectrotemporal modulations of song.

62 in the inferior colliculus (IC) are avoiding spectrotemporal modulations that are redundant across di

63 d speech reveals logarithmically distributed spectrotemporal modulations that can cover several order

64 ortex are informative of distinctive sets of spectrotemporal modulations.

65 We then developed a method to identify the spectrotemporal nature of these interactions and found t

66 retch imaging technology utilizes nonuniform spectrotemporal optical operations to compress the image

67 l engine for the segregation and matching of spectrotemporal patterns.

68 d provide a potential mechanism for learning spectrotemporal patterns.

69 Static spatial and spectrotemporal processes were able to fully explain mot

70 ar combination of static spatial mechanisms, spectrotemporal processes, and their interaction.

71 sensorimotor deficits, specifically auditory spectrotemporal processing deficits, cause phonological

72 This work illustrates organization of spectrotemporal processing in the human STG, and illumin

73 to characterize the spatial organization of spectrotemporal processing of speech across human STG, w

74 r speech perception, yet the organization of spectrotemporal processing of speech within the STG is n

75 However, the gross organization of spectrotemporal processing of speech within the STG is n

76 rate of frequency change indicating abnormal spectrotemporal processing.

77 es and acquired firing patterns suggest that spectrotemporal properties of a CS can control the essen

78 tation-maximization algorithm, we prove that spectrotemporal pursuit converges to the global MAP esti

79 Spectrotemporal pursuit offers a robust spectral decompo

80 We show that spectrotemporal pursuit works by applying to the time se

81 Our spectral decomposition procedure, termed spectrotemporal pursuit, can be efficiently computed usi

82 ocal subnetworks using cross-correlation and spectrotemporal receptive field (STRF) analysis for neig

83 Spectrotemporal receptive field (STRF) mapping describes

84 ly characterize response attributes with the spectrotemporal receptive field (STRF) methods to a rich

85 previous studies identified a limited set of spectrotemporal receptive field (STRF) types, but whethe

86 ques, we estimated the linear component, the spectrotemporal receptive field (STRF), of the transform

87 These task- and-stimulus-related spectrotemporal receptive field changes occurred only in

88 dated against pure tone receptive fields and spectrotemporal receptive field estimates in the inferio

89 we simulated neural responses using several spectrotemporal receptive field models that incorporated

90 scriminated stimulus categories, by changing spectrotemporal receptive field properties to encode bot

91 t primary auditory cortex (AI) and estimated spectrotemporal receptive fields (STRFs) and associated

92 ripple stimulus and constructed single-unit spectrotemporal receptive fields (STRFs) and their assoc

93 We characterized cat AI spectrotemporal receptive fields (STRFs) by finding both

94 nt study, we examined changes in a series of spectrotemporal receptive fields (STRFs) gathered from s

95 eptual ability by measuring rapid changes of spectrotemporal receptive fields (STRFs) in primary audi

96 The spectrotemporal receptive fields (STRFs) of NA neurons e

97 We used spectrotemporal receptive fields (STRFs) to study the ne

98 ocity of complex signals by extracting their spectrotemporal receptive fields (STRFs) using a family

99 c song, measured their tuning by calculating spectrotemporal receptive fields (STRFs), and classified

100 eurons are often described in terms of their spectrotemporal receptive fields (STRFs).

101 d not yield sustained activation of the STG, spectrotemporal receptive fields could be reconstructed

102 changes in response rates, as adaptations of spectrotemporal receptive fields following stimulation b

103 and neuronal input-output analysis based on spectrotemporal receptive fields revealed inhibition to

104 cortex neurons can be characterized by their spectrotemporal receptive fields, the spectral and tempo

105 logical extension to earlier observations of spectrotemporal receptive fields, which characterize the

106 mporal domain than is seen in their standard spectrotemporal receptive fields.

107 lective, persistent, task-related changes in spectrotemporal receptive fields.

108 ns, in this study, we sought to estimate the spectrotemporal regions in which sound statistics lead t

109 modulation in auditory belt cortex links the spectrotemporal representation of the whole acoustic sce

110 d and matching these components with learned spectrotemporal representations.

111 r model neurons exhibit the same tradeoff in spectrotemporal resolution as has been observed in IC.

112 njugate, and multiplexed biosensing based on spectrotemporal resolution of QD-FRET without requiring

113 ed by measuring focal changes in each cell's spectrotemporal response field (STRF) in a series of pas

114 ese two stimulus dimensions, we measured the spectrotemporal response fields (STRFs) associated with

115 e adapt new computational methods to map the spectrotemporal response fields of neurons in the audito

116 we report rapid, automatic plasticity of the spectrotemporal response of recorded neural ensembles, d

117 ization cue values and the neurons' binaural spectrotemporal response properties.

118 he first, to our knowledge, to show auditory spectrotemporal selectivity to natural stimuli in SC neu

119 aged STRFs revealed that temporal precision, spectrotemporal separability, and feature selectivity va

120 First, local spectrotemporal signal structure is differentially proce

121 standing of the transformation from auditory spectrotemporal signals to higher-order information such

122 coustic scene incorporating a broad range of spectrotemporal sound features.

123 rior colliculus (ICC) in response to dynamic spectrotemporal sound sequences to determine whether ICC

124 Figure and background signals overlap in spectrotemporal space, but vary in the statistics of flu

125 of a "figure" and background that overlap in spectrotemporal space, such that the only way to segrega

126 elective than the average thalamic spike for spectrotemporal stimulus features.

127 erns of rapid plasticity reflect closely the spectrotemporal structure of the task stimuli, thus exte

128 th, amplitude, and duration but differing in spectrotemporal structure.

129 sounds, suggesting tuning to speech-specific spectrotemporal structure.

130 increased selectivity for particular complex spectrotemporal structures, and may constitute an import

131 t anterior-posterior spatial distribution of spectrotemporal tuning in which the posterior STG is tun

132 d linear model, we were able to estimate the spectrotemporal tuning of excitatory and inhibitory inpu

133 During the processing of noise, spectrotemporal tuning was highly variable across cells.

134 raining modified circuitry that had combined spectrotemporal tuning, and therefore that circuits with

135 ble physiological evidence for such combined spectrotemporal tuning.

136 the nature of these changes using simplified spectrotemporal versions (upward vs downward shifting to