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Diagrammatic representation of pseudorandom stimulus sequences. (a) A non-conditioning sequence during which no noises are played. (b) An unpaired sequence, identical to (a), except that four noise bursts are played midway between tones. (c) A conditioning sequence, identical to (a) and (b) except that the four noise bursts occur immediately following low-frequency tones. In (c) the tone frequency paired with the noise (CS+) is played in the 90 s scanning window. In (d), a conditioning sequence similar to (c), the tone frequency explicitly unpaired with noise (CS7) is presented during scanning. Noises never occur in any of the scanning windows. H represents high-frequency tones; L represents lowfrequency tones; * represents noise burst; +++ represents scanning window.
Source publication
Experience-dependent plasticity of receptive fields in the auditory cortex has been demonstrated by electrophysiological experiments in animals. In the present study we used PET neuroimaging to measure regional brain activity in volunteer human subjects during discriminatory classical conditioning of high (8000 Hz) or low (200 Hz) frequency tones b...
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Citations
... The distribution of memory components among multiple neurons may evolve as an organizing principle in memory formation and storage. In flies, olfactory memories are encoded using a distributed code within the mushroom body (Bilz et al., 2020), and in mammalian brains, it is assumed that engram cells, the set of memory-storing neurons, are also widely distributed in the brain Josselyn and Tonegawa, 2020: the valence component in the amygdala (Liu et al., 2012), and the stimulus-specific information in sensory cortices (Jones et al., 2008;Morris et al., 1998;Ohl and Scheich, 2005;Sacco and Sacchetti, 2010 Changes in AWC ON responses are concentration-specific and depend on intact neural transmission ...
A major goal in neuroscience is to elucidate the principles by which memories are stored in a neural network. Here, we have systematically studied how four types of associative memories (short- and long-term memories, each as positive and negative associations) are encoded within the compact neural network of Caenorhabditis elegans worms. Interestingly, sensory neurons were primarily involved in coding short-term, but not long-term, memories, and individual sensory neurons could be assigned to coding either the conditioned stimulus or the experience valence (or both). Moreover, when considering the collective activity of the sensory neurons, the specific training experiences could be decoded. Interneurons integrated the modulated sensory inputs and a simple linear combination model identified the experience-specific modulated communication routes. The widely distributed memory suggests that integrated network plasticity, rather than changes to individual neurons, underlies the fine behavioral plasticity. This comprehensive study reveals basic memory-coding principles and highlights the central roles of sensory neurons in memory formation.
... These findings highlight the intriguing perspective that sensory systems are actively participating to encode associative memories. In mammals, similar stimulus-specific neuroplasticity was observed in primary sensory cortices (Morris, Friston and Dolan, 1998;Ohl and Scheich, 2005) and in peripheral sensory neurons (Jones et al. , 2008) . Thus, 20 . ...
A major goal in neuroscience is to elucidate the principles by which memories are stored in a neural network. Here, we have systematically studied how the four types of associative memories (short- and long-term memories, each formed using positive and negative associations) are encoded within the compact neural network of C. elegans worms. Interestingly, short-term, but not long-term, memories are evident in the sensory system. Long-term memories are relegated to inner layers of the network, allowing the sensory system to resume innate functionality. Furthermore, a small set of sensory neurons is allocated for coding short-term memories, a design that can increase memory capacity and limit non-innate behavioral responses. Notably, individual sensory neurons may code for the conditioned stimulus or the experience valence. Interneurons integrate these information to modulate animal behavior upon memory reactivation. This comprehensive study reveals basic principles by which memories are encoded within a neural network, and highlights the central roles of sensory neurons in memory formation.
... However, both fear acquisition and extinction induce plastic changes in a wider brain network, including the brain's sensory systems [4][5][6] . This is well documented in the primary and extended auditory cortex for rodents [7][8][9][10][11][12][13] and in few neuroimaging studies in humans [14][15][16][17] . By contrast, much less is known about the role of the visual cortex in associative memory and fear conditioning 5 . ...
Neurons in the visual cortex sharpen their orientation tuning as humans learn aversive contingencies. A stimulus orientation (CS+) that reliably predicts an aversive noise (unconditioned stimulus: US) is selectively enhanced in lower-tier visual cortex, while similar unpaired orientations (CS−) are inhibited. Here, we examine in male volunteers how sharpened visual processing is affected by fear extinction learning (where no US is presented), and how fear and extinction memory undergo consolidation one day after the original learning episode. Using steady-state visually evoked potentials from electroencephalography in a fear generalization task, we found that extinction learning prompted rapid changes in orientation tuning: Both conditioned visuocortical and skin conductance responses to the CS+ were strongly reduced. Next-day re-testing (delayed recall) revealed a brief but precise return-of-tuning to the CS+ in visual cortex accompanied by a brief, more generalized return-of-fear in skin conductance. Explorative analyses also showed persistent tuning to the threat cue in higher visual areas, 24 h after successful extinction, outlasting peripheral responding. Together, experience-based changes in the sensitivity of visual neurons show response patterns consistent with memory consolidation and spontaneous recovery, the hallmarks of long-term neural plasticity.
... Several quantification methods for PET tracer kinetic modeling have been previously established [7,38,42] and were either based on compartment model analyses utilizing a metabolite-corrected arterial input function [39,43] or on reference tissue models [41,44]. Comparisons between models with blood based input data and reference tissue models have been made demonstrating that reference tissue models can provide an adequate replacement for investigating receptor binding in both humans [22,[44][45][46][47] and rats [38,44,48]. ...
Purpose
Plastic changes in the central auditory system involving the GABAergic system accompany age-related hearing loss. Such processes can be investigated with positron emission tomography (PET) imaging using [¹⁸F]flumazenil ([¹⁸F]FMZ). Here, [¹⁸F]FMZ PET-based modeling approaches allow a simple and reliable quantification of GABAA receptor binding capacity revealing regional differences and age-related changes.
Procedures
Sixty-minute list-mode PET acquisitions were performed in 9 young (range 5–6 months) and 11 old (range 39–42 months) gerbils, starting simultaneously with the injection of [¹⁸F]FMZ via femoral vein. Non-displaceable binding potentials (BPnd) with pons as reference region were calculated for auditory cortex (AC), inferior colliculus (IC), medial geniculate body (MGB), somatosensory cortex (SC), and cerebellum (CB) using (i) a two-tissue compartment model (2TCM), (ii) the Logan plot with image-derived blood-input (Logan (BI)), (iii) a simplified reference tissue model (SRTM), and (iv) the Logan reference model (Logan (RT)). Statistical parametric mapping analysis (SPM) comparing young and old gerbils was performed using 3D parametric images for BPnd based on SRTM. Results were verified with in vitro autoradiography from five additional young gerbils. Model assessment included the Akaike information criterion (AIC). Hearing was evaluated using auditory brainstem responses.
Results
BPnd differed significantly between models (p < 0.0005), showing the smallest mean difference between 2TCM as reference and SRTM as simplified procedure. SRTM revealed the lowest AIC values. Both volume of distribution (r² = 0.8793, p = 0.018) and BPnd (r² = 0.8216, p = 0.034) correlated with in vitro autoradiography data. A significant age-related decrease of receptor binding was observed in auditory (AC, IC, MGB) and other brain regions (SC and CB) (p < 0.0001, unpaired t test) being confirmed by SPM using pons as reference (p < 0.0001, uncorrected).
Conclusion
Imaging of GABAA receptor binding capacity in gerbils using [¹⁸F]FMZ PET revealed SRTM as a simple and robust quantification method of GABAA receptors. Comparison of BPnd in young and old gerbils demonstrated an age-related decrease of GABAA receptor binding.
... The primary auditory cortex indirectly receives synaptic input from the amygdala through the basal ganglia cholinergic projections of the basal ganglia in the basal forebrain, regulating synaptic plasticity (Yan, 2003;Keuroghlian and Knudsen, 2007). Studies on rats have indeed shown that fear conditioning, which includes activation of the amygdala, augments tonotopic map plasticity in the auditory cortex (Morris et al., 1998;Froemke and Martins, 2011). In addition, rat studies have demonstrated that stimulation of the lateral amygdala can inhibit the response of the primary auditory cortex to sound via GABA receptors . ...
Tinnitus is thought to be triggered by aberrant neural activity in the central auditory pathway and is often accompanied by comorbidities of emotional distress and anxiety, which imply maladaptive functional connectivity to limbic structures, such as the amygdala and hippocampus. Tinnitus patients with normal audiograms can also have accompanying anxiety and depression, clinically. To test the role of functional connectivity between the central auditory pathway and limbic structures in patients with tinnitus with normal audiograms, we developed a murine noise-induced tinnitus model with a temporary threshold shift (TTS). Tinnitus mice exhibited reduced auditory brainstem response wave I amplitude, and an enhanced wave IV amplitude and wave IV/I amplitude ratio, as compared with control and non-tinnitus mice. Resting-state functional magnetic resonance imaging (fMRI) was used to identify abnormal connectivity of the amygdala and hippocampus and to determine the relationship with tinnitus characteristics. We found increased fMRI responses with amplitude of low-frequency fluctuation (ALFF) in the auditory cortex and decreased ALFF in the amygdala and hippocampus at day 1, but decreased ALFF in the auditory cortex and increased ALFF in the amygdala at day 28 post-noise exposure in tinnitus mice. Decreased functional connectivity between auditory brain regions and limbic structures was demonstrated at day 28 in tinnitus mice. Therefore, aberrant neural activities in tinnitus mice with TTS involved not only the central auditory pathway, but also limbic structures, and there was maladaptive functional connectivity between the central auditory pathway and limbic structures, such as the amygdala and hippocampus.
... Early studies used relatively short durations of 40 s [2,4]. In many studies up to now, intermediate durations between 60 and 90 s are employed [14,17,[26][27][28][29][30][31]. Working groups from Japan often use 120 s acquisition time [8,[32][33][34]. ...
... A further issue is smoothing of the three-dimensional (3D) data set during preprocessing. Filter kernels between 1 and 2 times of the spatial resolution (FWHM, full width at half maximum) of the used PET scanner (7-12 mm) tended to be more frequently employed [15,17,[27][28][29][30][31] as compared to kernels between 2-and 3-fold the FWHM (15-20 mm) [14,[35][36][37]. ...
... Finally, the cut-off used for statistical inferences from statistical parametric maps is variable. Although a p value less than 0.001 uncorrected for multiple comparisons is frequently employed [14,15,29,38], less rigid thresholds have been applied as well [28,30,31,37]. ...
Background:
15O-Water positron emission tomography (PET) enables functional imaging of the auditory system during stimulation via a promontory electrode or cochlear implant, which is not possible using functional magnetic resonance imaging (fMRI). Although PET has been introduced in this context decades ago, its feasibility when performed during general anesthesia has not yet been explored. However, due to a shift to earlier (and bilateral) auditory implantation, the need to study children during general anesthesia appeared, since they are not able to cooperate during scanning. Therefore, we evaluated retrospectively results of individual SPM (statistical parametric mapping) analysis of 15O-water PET in 17 children studied during general anesthesia and compared them to those in 9 adults studied while awake. Specifically, the influence of scan duration, smoothing filter kernel employed during preprocessing, and cut-off value used for statistical inferences were evaluated. Frequencies, peak heights, and extents of activations in auditory and extra-auditory brain regions (AR and eAR) were registered.
Results:
It was possible to demonstrate activations in auditory brain regions during general anesthesia; however, the frequency and markedness of positive findings were dependent on some of the abovementioned influence factors. Scan duration (60 vs. 90 s) had no significant influence on peak height of auditory cortex activations. To achieve a similar frequency and extent of AR activations during general anesthesia compared to waking state, a lower cut-off for statistical inferences (p < 0.05 or p < 0.01 vs. p < 0.001) had to be applied. However, this lower cut-off was frequently associated with unexpected, "artificial" activations in eAR. These activations in eAR could be slightly reduced by the use of a stronger smoothing filter kernel during preprocessing of the data (e.g., [30 mm]3).
Conclusions:
Our data indicate that it is feasible to detect auditory cortex activations in 15O-water PET during general anesthesia. Combined with the improved signal to noise ratios of modern PET scanners, this suggests reasonable prospects for further evaluation of the method for clinical use in auditory implant users. Adapted parameters for data analysis seem to be helpful to improve the proportion of signals in AR versus eAR.
... Numerous studies reveal that the primary auditory cortex (area A1) undergoes modifications that parallel the animal's emotional experiences with sound (Diamond and Weinberger, 1986;Bakin and Weinberger, 1990;Edelin & Weinberger, 1993;Gao and Suga, 2000;Kisley and Gerstein, 2001;Tzounopoulos and Leăo, 2012;McGann, 2016). If conditioned responding develops to a tone stimulus that has become a reliable predictor of a rewarding or punishing event, an alteration in the tonotopic map may ensue, as the area of cortex devoted to processing the tone's frequency undergoes expansion (Recanzone et al., 1993;Morris et al., 1998;Rutkowski and Weinberger, 2005;Reed et al., 2011;Bieszczad and Weinberger, 2012, also see Weinberger, 2015, for a review). Other forms of plasticity may emerge following auditory learning, such as a reduction in neural thresholds, or a decrease in tuning bandwidth (sharpening of tuning) for frequencies deemed relevant to an animal (Froemke et al., 2013;Voss et al., 2015), as well as a reduction in cortical synaptic inhibition (Sarro et al., 2015). ...
The current report provides a detailed analysis of the changes in the first two components of the auditory evoked potential (AEP) that accompany associative learning. AEPs were recorded from the primary auditory cortex before and after training sessions. Experimental subjects underwent one (n = 5) or two (n = 7) days of conditioning in which a tone, serving as a conditioned stimulus (CS), was paired with mild foot shock. Control subjects received one (n = 5) or two (n = 7) days of exposure to the same stimuli delivered randomly. Only animals receiving paired CS-US training developed a conditioned tachycardia response to the tone. Our analyses demonstrated that both early components of the AEP recorded from the granular layer of the cortex undergo CS-specific associative changes: (1) the first, negative component (occurring ∼21 ms following tone onset) was significantly augmented after one and two days of training while maintaining its latency, and (2) the second, positive component (occurring ∼50 ms following tone onset) was augmented after two days of training, and showed a significant reduction in latency after one and two days of training. We view these changes as evidence of increased cortical synchronization, thereby lending new insight into the temporal dynamics of neural network activity related to auditory learning.
... Rodent studies have demonstrated that fearconditioning can activate the amygdala and may improve tonotopic map plasticity in the auditory cortex. The receptive fields for frequencies of unconditioned stimuli were enhanced by co-activity of the basal forebrain and auditory cortex (80)(81)(82)(83). It was also demonstrated that stimulation of the lateral amygdala can inhibit the primary auditory cortex response to sound by means of GABA receptors (84). ...
Our knowledge about subjective tinnitus physiopathology has improved in the last decades, while information to understand the main mechanisms that transform a neutral phantom sound to tinnitus distress appear to be inadequate. The current review presents evidence from several studies using neuroimaging, electrophysiology
and brain lesion techniques aiming at hypothesizing a new realistic multimodality tinnitus framework which can better explain the structural and functional brain connectivity in different stages of tinnitus development. Further to the present work, a full review of the entire literature should be prompted to discuss evidence to more
comprehensively investigate the relationship between structural and functional connectivity of tinnitus. Progresses in such framework will shed lights to the tinnitus neurofunctional model and further evidence-based treatment modalities.
... However, associative learning has now been shown to induce sophisticated stimulus-specific neuroplasticity in the mammalian auditory, visual, olfactory, somatosensory, and gustatory systems, which are only indirectly related to behavior. These effects have been observed not only in secondary sensory "association" cortices (Sacco and Sacchetti 2010) but also in primary sensory cortices (Morris et al. 1998;Ohl and Scheich 2005;Polley et al. 2007;Li et al. 2008;Chen et al. 2011;Gdalyahu et al. 2012;Suga 2012;Weinberger 2015), subcortical sensory structures (Edeline andWeinberger 1991a,b, 1992;Cruikshank et al. 1992;Kay and Laurent 1999;Gao and Suga 2000;Doucette et al. 2011;Fletcher 2012), and even primary sensory neurons (Jones et al. 2008;Kass et al. 2013d;Dias and Ressler 2014). ...
... If no further training occurs the naturally occurring expansion lasts for weeks, but extinction training, in which the subject learns that the CS no longer predicts the reward, reverses the cortical remapping (Bieszczad and Weinberger 2012). Similar work used classical conditioning in a PET scanner to train human subjects that high-or low-frequency tones predicted an aversive white noise burst and observed frequency-specific changes in auditory-evoked responses in the auditory cortex (Morris et al. 1998), though longer-term imaging experiments in humans have not been possible. ...
Historically, the body's sensory systems have been presumed to provide the brain with raw information about the external environment, which the brain must interpret to select a behavioral response. Consequently, studies of the neurobiology of learning and memory have focused on circuitry that interfaces between sensory inputs and behavioral outputs, such as the amygdala and cerebellum. However, evidence is accumulating that some forms of learning can in fact drive stimulus-specific changes very early in sensory systems, including not only primary sensory cortices but also precortical structures and even the peripheral sensory organs themselves. This review synthesizes evidence across sensory modalities to report emerging themes, including the systems' flexibility to emphasize different aspects of a sensory stimulus depending on its predictive features and ability of different forms of learning to produce similar plasticity in sensory structures. Potential functions of this learning-induced neuroplasticity are discussed in relation to the challenges faced by sensory systems in changing environments, and evidence for absolute changes in sensory ability is considered. We also emphasize that this plasticity may serve important nonsensory functions, including balancing metabolic load, regulating attentional focus, and facilitating downstream neuroplasticity.
... 4. При выполнении требующей внимания задачи на дискриминацию тонов выявлено коррелированное увеличение активности в ответ на тоны определенной частоты в тонотопических слуховых областях и в орбитофронтальной коре [79]. При предъявлении стимула-мишени, в отличие от предъявления дистрактора, сильное увеличение активности наблюдалось и в тонотопических областях высокого порядка в дорзальной части задней эктосильвиевой извилины [13]. ...
A hypothetical mechanism is suggested for processing of complex sounds and auditory attention in parallel
neuronal loops including various auditory cortical areas connected with parts of the medial geniculate
body, inferior colliculus and basal ganglia. Release of dopamine in the striatum promotes bidirectional
modulation of strong and weak inputs from the neocortex to striatal neurons giving rise to direct and
indirect pathways through the basal ganglia. Subsequent synergistic disinhibition of one and inhibition
of other groups of thalamic neurons by the basal ganglia result in the creation of contrasted neuronal
representations of properties of auditory stimuli in related cortical areas. Contrasting is strengthened
due to a simultaneous disinhibition of pedunculopontine nucleus and action at muscarine receptors on
neurons in the medial geniculate body. It follows from this mechanism that involuntary attention to
sound tone can enhance an early component of the responses of neurons in the primary auditory cortical
area (50 msec) in the absence of dopamine due to a disinhibition of thalamic neurons via the direct
pathway through the basal ganglia, whereas voluntary attention to complex sounds can enhance only
those components of responses of neurones in secondary auditory cortical areas which latencies exceeds
latencies of dopaminergic cells (i.e. after 100 msec). Various consequences of proposed mechanism are
in agreement with known experimental data.
