tivation of the left and right posterior parietal cortex, suggesting that these regions perform d... more tivation of the left and right posterior parietal cortex, suggesting that these regions perform distinct functions in this imagery task. This is confirmed by a trialby-trial analysis of correlations between reaction time and onset, width, and amplitude of the hemodynamic response. These findings pose neurophysiological constraints on cognitive models of mental imagery.
The formation of new sound categories is fundamental to everyday goal-directed behavior. Categori... more The formation of new sound categories is fundamental to everyday goal-directed behavior. Categorization requires the abstraction of discrete classes from continuous physical features as required by context and task. Electrophysiology in animals has shown that learning to categorize novel sounds alters their spatiotemporal neural representation at the level of early auditory cortex. However, functional magnetic resonance imaging (fMRI) studies so far did not yield insight into the effects of category learning on sound representations in human auditory cortex. This may be due to the use of overlearned speech-like categories and fMRI subtraction paradigms, leading to insufficient sensitivity to distinguish the responses to learning-induced, novel sound categories. Here, we used fMRI pattern analysis to investigate changes in human auditory cortical response patterns induced by category learning. We created complex novel sound categories and analyzed distributed activation patterns during passive listening to a sound continuum before and after category learning. We show that only after training, sound categories could be successfully decoded from early auditory areas and that learning-induced pattern changes were specific to the category-distinctive sound feature (i.e., pitch). Notably, the similarity between fMRI response patterns for the sound continuum mirrored the sigmoid shape of the behavioral category identification function. Our results indicate that perceptual representations of novel sound categories emerge from neural changes at early levels of the human auditory processing hierarchy.
2012 Second International Workshop on Pattern Recognition in NeuroImaging, 2012
So far, most fMRI studies that analyzed voxel activity patterns of more than two conditions trans... more So far, most fMRI studies that analyzed voxel activity patterns of more than two conditions transformed the multiclass problem into a series of binary problems. Furthermore, visualizations of the topology of underlying representations are usually not presented. Here, we explore the feasibility of different types of supervised self-organizing maps (SSOM) to decode and visualize voxel patterns of fMRI datasets consisting of multiple conditions. Our results suggest thatcompared to commonly applied classification approaches -SSOMs are well suited when activity patterns consist of a small number of features (e.g. as in searchlight-or region of interestbased approaches). In addition, we demonstrate the utility of using SOM grids for intuitive and exploratory visualization of topological relations among classes of fMRI activity patterns.
In the last few years, novel functional neuroimaging techniques have provided powerful tools for ... more In the last few years, novel functional neuroimaging techniques have provided powerful tools for the noninvasive investigation of brain anatomy and function. In particular, functional Magnetic Resonance Imaging (fMRI) has rapidly assumed a leading role among these techniques and has been extensively used to gain insights on the functions of the normal brain. Here we discuss: 1) the possibility of using this technique as a tool for assessing the processes of cortical reorganization that occur in impaired patients that follow programs of cognitive rehabilitation. 2) the possibility of using realtime fMRI for biofeedback applications.
ABSTRACT Rationale: Generalized spike wave discharges (GSW) are the electroencephalographic hallm... more ABSTRACT Rationale: Generalized spike wave discharges (GSW) are the electroencephalographic hallmark of idiopathic generalized epilepsy (IGE) and are also seen in secondarily generalized epilepsy (SGE). The pathophysiological substrate of GSW remains enigmatic and the debate between subcortical (the “centroencephalic hypothesis”) and cortical origins remains open [1]. The findings of a number of studies indicate that the prefrontal cortex (BA10 and BA32) may be involved in the generation of GSW [2]. In this work we analysed fMRI data using dynamic causal modelling (DCM) to investigate the effective connectivity between thalamus and frontal cortex in patients with GSW. Methods: We selected EEG-fMRI data from 8 patients (4 IGE and 4 SGE) with frequent GSW discharges which had shown significant GSW-correlated haemodynamic signal changes (activation or deactivation) in the thalamus, the frontal cortex (medial frontal gyrus-BA10) and precuneus in previous GSW-correlated analyses [3] Using DCM we assessed the effective connectivity, i.e. which region drives another region. Neuronal activity was modelled using the known inputs (GSW) and outputs (haemodynamic responses measured with fMRI). Two DCM pairs (four models) per patient were constructed (using ROIs derived from statistical parametric maps resulted from GLM analysis) each comprising two structurally connected regions (5 mm diameter spheres): a) thalamus and BA10: changes in the states of BA10 depend on the activity of the thalamus or vice versa; b) thalamus and precuneus: changes in the states of precuneus depend on the activity of the thalamus or vice versa. For each model, this dependency was parameterized considering GSW both as driving and modulatory effects. For each model, we computed its likelihood. Results: No consistent evidence in favour of any directional thalamus and BA10 modulation was found in 6 out of 8 patients (4 SGE and 2 IGE). In the other 2 patients (IGE) we found strong evidence for the model in which BA10 activity was driven by the thalamus. In 6 patients (3 IGE and 3 SGE), there was strong evidence for the model in which thalamic activity depended on the precuneal state but not vice versa. In the remaining two cases no consistent evidence in favour of any directional model was found. Conclusions: Given the tested models, our findings suggest that during sustained GSW there is no unidirectional connectivity between the thalamus and the frontal cortex but that thalamic activity is driven by the state of the precuneus. These data support the established hypothesis that both thalamus and cortex are equally involved during GSW in a reverberating corticosubcortical loop. Moreover our findings suggest this thalamo-cortical activity is influenced by the precuneus, a key region related to vigilance and consciousness. References: [1] H Meeren et al. Arch Neurol, 2005, 62; 371–376. [2] MD Holmes et al. Epilepsia 2004, 45(12); 1568–1579. [3] K Hamandi et al. Neuroimage 2006, 31; 1700–1710.
We thank the commentators (Friston, this issue; David, this issue) for their thoughtful discussio... more We thank the commentators (Friston, this issue; David, this issue) for their thoughtful discussion and careful detailing of their arguments and views on issues of connectivity analysis and causality. We limit ourselves here to specific replies to comments and refer to other contributions in this section for both further detail and overview.
It has been proposed that enhanced activity in the human motion complex (hMT + /V5) underlies the... more It has been proposed that enhanced activity in the human motion complex (hMT + /V5) underlies the perception of illusory motion. Recent studies, however, have argued that in the case of motion aftereffect (MAE) this increase is due to visual selective attention rather than to the ...
Multivariate regression is increasingly used to study the relation between fMRI spatial activatio... more Multivariate regression is increasingly used to study the relation between fMRI spatial activation patterns and experimental stimuli or behavioral ratings. With linear models, informative brain locations are identified by mapping the model coefficients. This is a central aspect in neuroimaging, as it provides the sought-after link between the activity of neuronal populations and subject's perception, cognition or behavior. Here, we show that mapping of informative brain locations using multivariate linear regression (MLR) may lead to incorrect conclusions and interpretations. MLR algorithms for high dimensional data are designed to deal with targets (stimuli or behavioral ratings, in fMRI) separately, and the predictive map of a model integrates information deriving from both neural activity patterns and experimental design. Not accounting explicitly for the presence of other targets whose associated activity spatially overlaps with the one of interest may lead to predictive maps of troublesome interpretation. We propose a new model that can correctly identify the spatial patterns associated with a target while achieving good generalization. For each target, the training is based on an augmented dataset, which includes all remaining targets. The estimation on such datasets produces both maps and interaction coefficients, which are then used to generalize. The proposed formulation is independent of the regression algorithm employed. We validate this model on simulated fMRI data and on a publicly available dataset. Results indicate that our method achieves high spatial sensitivity and good generalization and that it helps disentangle specific neural effects from interaction with predictive maps associated with other targets.
There is an increasing interest to integrate electrophysiological and hemodynamic measures for ch... more There is an increasing interest to integrate electrophysiological and hemodynamic measures for characterizing spatial and temporal aspects of cortical processing. However, an informative combination of responses that have markedly different sensitivities to the underlying neural activity is not straightforward, especially in complex cognitive tasks. Here, we used parametric stimulus manipulation in magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) recordings on the same subjects, to study effects of noise on processing of spoken words and environmental sounds. The added noise influenced MEG response strengths in the bilateral supratemporal auditory cortex, at different times for the different stimulus types. Specifically for spoken words, the effect of noise on the electrophysiological response was remarkably nonlinear. Therefore, we used the singlesubject MEG responses to construct parametrization for fMRI data analysis and obtained notably higher sensitivity than with conventional stimulus--based parametrization. fMRI results showed that partly different temporal areas were involved in noise-sensitive processing of words and environmental sounds. These results indicate that cortical processing of sounds in background noise is stimulus specific in both timing and location and provide a new functionally meaningful platform for combining information obtained with electrophysiological and hemodynamic measures of brain function.
In combination with cognitive tasks entailing sequences of sensory and cognitive processes, event... more In combination with cognitive tasks entailing sequences of sensory and cognitive processes, event-related acquisition schemes allow using functional MRI to examine,not only the topography but also the temporal sequence of cortical activation across brain regions (time-resolved fMRI). In this study, we compared two data-driven methods — fuzzy clustering method (FCM) and independent component analysis (ICA) — in the context
Non-invasive brain stimulation with transcranial alternating currents (tACS) has been shown to en... more Non-invasive brain stimulation with transcranial alternating currents (tACS) has been shown to entrain slow cortical oscillations and thereby influence various aspects of visual perception. Much less is known about its potential effects on auditory perception. In the present study, we apply a novel variant that enables near-equivalent stimulation of both auditory cortices to investigate the causal role of the phase of 4-Hz cortical oscillations for auditory perception. We measured detection performance for near-threshold auditory stimuli (4-Hz click trains) that were presented at various moments during ongoing tACS (two synchronous 4-Hz alternating currents applied transcranially to the two cerebral hemispheres). We found that changes in the relative timing of acoustic and electric stimulation cause corresponding perceptual changes that oscillate predominantly at the 4-Hz frequency of the electric stimulation, which is consistent with previous results based on 10-Hz tACS. TACS at va...
While advances in magnetic resonance imaging (MRI) throughout the last decades have enabled the d... more While advances in magnetic resonance imaging (MRI) throughout the last decades have enabled the detailed anatomical and functional inspection of the human brain non-invasively, to date there is no consensus regarding the precise subdivision and topography of the areas forming the human auditory cortex. Here, we propose a topography of the human auditory areas based on insights on the anatomical and functional properties of human auditory areas as revealed by studies of cyto- and myelo-architecture and fMRI investigations at ultra-high magnetic field (7 Tesla). Importantly, we illustrate that-whereas a group-based approach to analyze functional (tonotopic) maps is appropriate to highlight the main tonotopic axis-the examination of tonotopic maps at single subject level is required to detail the topography of primary and non-primary areas that may be more variable across subjects. Furthermore, we show that considering multiple maps indicative of anatomical (i.e., myelination) as well ...
The transformation of acoustic signals into abstract perceptual representations is the essence of... more The transformation of acoustic signals into abstract perceptual representations is the essence of the efficient and goal-directed neural processing of sounds in complex natural environments. While the human and animal auditory system is perfectly equipped to process the spectrotemporal sound features, adequate sound identification and categorization require neural sound representations that are invariant to irrelevant stimulus parameters. Crucially, what is relevant and irrelevant is not necessarily intrinsic to the physical stimulus structure but needs to be learned over time, often through integration of information from other senses. This review discusses the main principles underlying categorical sound perception with a special focus on the role of learning and neural plasticity. We examine the role of different neural structures along the auditory processing pathway in the formation of abstract sound representations with respect to hierarchical as well as dynamic and distribute...
The Journal of neuroscience : the official journal of the Society for Neuroscience, Jan 10, 2012
Auditory cortical processing of complex meaningful sounds entails the transformation of sensory (... more Auditory cortical processing of complex meaningful sounds entails the transformation of sensory (tonotopic) representations of incoming acoustic waveforms into higher-level sound representations (e.g., their category). However, the precise neural mechanisms enabling such transformations remain largely unknown. In the present study, we use functional magnetic resonance imaging (fMRI) and natural sounds stimulation to examine these two levels of sound representation (and their relation) in the human auditory cortex. In a first experiment, we derive cortical maps of frequency preference (tonotopy) and selectivity (tuning width) by mathematical modeling of fMRI responses to natural sounds. The tuning width maps highlight a region of narrow tuning that follows the main axis of Heschl's gyrus and is flanked by regions of broader tuning. The narrowly tuned portion on Heschl's gyrus contains two mirror-symmetric frequency gradients, presumably defining two distinct primary auditory ...
The Journal of neuroscience : the official journal of the Society for Neuroscience, Jan 19, 2012
The formation of new sound categories is fundamental to everyday goal-directed behavior. Categori... more The formation of new sound categories is fundamental to everyday goal-directed behavior. Categorization requires the abstraction of discrete classes from continuous physical features as required by context and task. Electrophysiology in animals has shown that learning to categorize novel sounds alters their spatiotemporal neural representation at the level of early auditory cortex. However, functional magnetic resonance imaging (fMRI) studies so far did not yield insight into the effects of category learning on sound representations in human auditory cortex. This may be due to the use of overlearned speech-like categories and fMRI subtraction paradigms, leading to insufficient sensitivity to distinguish the responses to learning-induced, novel sound categories. Here, we used fMRI pattern analysis to investigate changes in human auditory cortical response patterns induced by category learning. We created complex novel sound categories and analyzed distributed activation patterns duri...
tivation of the left and right posterior parietal cortex, suggesting that these regions perform d... more tivation of the left and right posterior parietal cortex, suggesting that these regions perform distinct functions in this imagery task. This is confirmed by a trialby-trial analysis of correlations between reaction time and onset, width, and amplitude of the hemodynamic response. These findings pose neurophysiological constraints on cognitive models of mental imagery.
The formation of new sound categories is fundamental to everyday goal-directed behavior. Categori... more The formation of new sound categories is fundamental to everyday goal-directed behavior. Categorization requires the abstraction of discrete classes from continuous physical features as required by context and task. Electrophysiology in animals has shown that learning to categorize novel sounds alters their spatiotemporal neural representation at the level of early auditory cortex. However, functional magnetic resonance imaging (fMRI) studies so far did not yield insight into the effects of category learning on sound representations in human auditory cortex. This may be due to the use of overlearned speech-like categories and fMRI subtraction paradigms, leading to insufficient sensitivity to distinguish the responses to learning-induced, novel sound categories. Here, we used fMRI pattern analysis to investigate changes in human auditory cortical response patterns induced by category learning. We created complex novel sound categories and analyzed distributed activation patterns during passive listening to a sound continuum before and after category learning. We show that only after training, sound categories could be successfully decoded from early auditory areas and that learning-induced pattern changes were specific to the category-distinctive sound feature (i.e., pitch). Notably, the similarity between fMRI response patterns for the sound continuum mirrored the sigmoid shape of the behavioral category identification function. Our results indicate that perceptual representations of novel sound categories emerge from neural changes at early levels of the human auditory processing hierarchy.
2012 Second International Workshop on Pattern Recognition in NeuroImaging, 2012
So far, most fMRI studies that analyzed voxel activity patterns of more than two conditions trans... more So far, most fMRI studies that analyzed voxel activity patterns of more than two conditions transformed the multiclass problem into a series of binary problems. Furthermore, visualizations of the topology of underlying representations are usually not presented. Here, we explore the feasibility of different types of supervised self-organizing maps (SSOM) to decode and visualize voxel patterns of fMRI datasets consisting of multiple conditions. Our results suggest thatcompared to commonly applied classification approaches -SSOMs are well suited when activity patterns consist of a small number of features (e.g. as in searchlight-or region of interestbased approaches). In addition, we demonstrate the utility of using SOM grids for intuitive and exploratory visualization of topological relations among classes of fMRI activity patterns.
In the last few years, novel functional neuroimaging techniques have provided powerful tools for ... more In the last few years, novel functional neuroimaging techniques have provided powerful tools for the noninvasive investigation of brain anatomy and function. In particular, functional Magnetic Resonance Imaging (fMRI) has rapidly assumed a leading role among these techniques and has been extensively used to gain insights on the functions of the normal brain. Here we discuss: 1) the possibility of using this technique as a tool for assessing the processes of cortical reorganization that occur in impaired patients that follow programs of cognitive rehabilitation. 2) the possibility of using realtime fMRI for biofeedback applications.
ABSTRACT Rationale: Generalized spike wave discharges (GSW) are the electroencephalographic hallm... more ABSTRACT Rationale: Generalized spike wave discharges (GSW) are the electroencephalographic hallmark of idiopathic generalized epilepsy (IGE) and are also seen in secondarily generalized epilepsy (SGE). The pathophysiological substrate of GSW remains enigmatic and the debate between subcortical (the “centroencephalic hypothesis”) and cortical origins remains open [1]. The findings of a number of studies indicate that the prefrontal cortex (BA10 and BA32) may be involved in the generation of GSW [2]. In this work we analysed fMRI data using dynamic causal modelling (DCM) to investigate the effective connectivity between thalamus and frontal cortex in patients with GSW. Methods: We selected EEG-fMRI data from 8 patients (4 IGE and 4 SGE) with frequent GSW discharges which had shown significant GSW-correlated haemodynamic signal changes (activation or deactivation) in the thalamus, the frontal cortex (medial frontal gyrus-BA10) and precuneus in previous GSW-correlated analyses [3] Using DCM we assessed the effective connectivity, i.e. which region drives another region. Neuronal activity was modelled using the known inputs (GSW) and outputs (haemodynamic responses measured with fMRI). Two DCM pairs (four models) per patient were constructed (using ROIs derived from statistical parametric maps resulted from GLM analysis) each comprising two structurally connected regions (5 mm diameter spheres): a) thalamus and BA10: changes in the states of BA10 depend on the activity of the thalamus or vice versa; b) thalamus and precuneus: changes in the states of precuneus depend on the activity of the thalamus or vice versa. For each model, this dependency was parameterized considering GSW both as driving and modulatory effects. For each model, we computed its likelihood. Results: No consistent evidence in favour of any directional thalamus and BA10 modulation was found in 6 out of 8 patients (4 SGE and 2 IGE). In the other 2 patients (IGE) we found strong evidence for the model in which BA10 activity was driven by the thalamus. In 6 patients (3 IGE and 3 SGE), there was strong evidence for the model in which thalamic activity depended on the precuneal state but not vice versa. In the remaining two cases no consistent evidence in favour of any directional model was found. Conclusions: Given the tested models, our findings suggest that during sustained GSW there is no unidirectional connectivity between the thalamus and the frontal cortex but that thalamic activity is driven by the state of the precuneus. These data support the established hypothesis that both thalamus and cortex are equally involved during GSW in a reverberating corticosubcortical loop. Moreover our findings suggest this thalamo-cortical activity is influenced by the precuneus, a key region related to vigilance and consciousness. References: [1] H Meeren et al. Arch Neurol, 2005, 62; 371–376. [2] MD Holmes et al. Epilepsia 2004, 45(12); 1568–1579. [3] K Hamandi et al. Neuroimage 2006, 31; 1700–1710.
We thank the commentators (Friston, this issue; David, this issue) for their thoughtful discussio... more We thank the commentators (Friston, this issue; David, this issue) for their thoughtful discussion and careful detailing of their arguments and views on issues of connectivity analysis and causality. We limit ourselves here to specific replies to comments and refer to other contributions in this section for both further detail and overview.
It has been proposed that enhanced activity in the human motion complex (hMT + /V5) underlies the... more It has been proposed that enhanced activity in the human motion complex (hMT + /V5) underlies the perception of illusory motion. Recent studies, however, have argued that in the case of motion aftereffect (MAE) this increase is due to visual selective attention rather than to the ...
Multivariate regression is increasingly used to study the relation between fMRI spatial activatio... more Multivariate regression is increasingly used to study the relation between fMRI spatial activation patterns and experimental stimuli or behavioral ratings. With linear models, informative brain locations are identified by mapping the model coefficients. This is a central aspect in neuroimaging, as it provides the sought-after link between the activity of neuronal populations and subject's perception, cognition or behavior. Here, we show that mapping of informative brain locations using multivariate linear regression (MLR) may lead to incorrect conclusions and interpretations. MLR algorithms for high dimensional data are designed to deal with targets (stimuli or behavioral ratings, in fMRI) separately, and the predictive map of a model integrates information deriving from both neural activity patterns and experimental design. Not accounting explicitly for the presence of other targets whose associated activity spatially overlaps with the one of interest may lead to predictive maps of troublesome interpretation. We propose a new model that can correctly identify the spatial patterns associated with a target while achieving good generalization. For each target, the training is based on an augmented dataset, which includes all remaining targets. The estimation on such datasets produces both maps and interaction coefficients, which are then used to generalize. The proposed formulation is independent of the regression algorithm employed. We validate this model on simulated fMRI data and on a publicly available dataset. Results indicate that our method achieves high spatial sensitivity and good generalization and that it helps disentangle specific neural effects from interaction with predictive maps associated with other targets.
There is an increasing interest to integrate electrophysiological and hemodynamic measures for ch... more There is an increasing interest to integrate electrophysiological and hemodynamic measures for characterizing spatial and temporal aspects of cortical processing. However, an informative combination of responses that have markedly different sensitivities to the underlying neural activity is not straightforward, especially in complex cognitive tasks. Here, we used parametric stimulus manipulation in magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) recordings on the same subjects, to study effects of noise on processing of spoken words and environmental sounds. The added noise influenced MEG response strengths in the bilateral supratemporal auditory cortex, at different times for the different stimulus types. Specifically for spoken words, the effect of noise on the electrophysiological response was remarkably nonlinear. Therefore, we used the singlesubject MEG responses to construct parametrization for fMRI data analysis and obtained notably higher sensitivity than with conventional stimulus--based parametrization. fMRI results showed that partly different temporal areas were involved in noise-sensitive processing of words and environmental sounds. These results indicate that cortical processing of sounds in background noise is stimulus specific in both timing and location and provide a new functionally meaningful platform for combining information obtained with electrophysiological and hemodynamic measures of brain function.
In combination with cognitive tasks entailing sequences of sensory and cognitive processes, event... more In combination with cognitive tasks entailing sequences of sensory and cognitive processes, event-related acquisition schemes allow using functional MRI to examine,not only the topography but also the temporal sequence of cortical activation across brain regions (time-resolved fMRI). In this study, we compared two data-driven methods — fuzzy clustering method (FCM) and independent component analysis (ICA) — in the context
Non-invasive brain stimulation with transcranial alternating currents (tACS) has been shown to en... more Non-invasive brain stimulation with transcranial alternating currents (tACS) has been shown to entrain slow cortical oscillations and thereby influence various aspects of visual perception. Much less is known about its potential effects on auditory perception. In the present study, we apply a novel variant that enables near-equivalent stimulation of both auditory cortices to investigate the causal role of the phase of 4-Hz cortical oscillations for auditory perception. We measured detection performance for near-threshold auditory stimuli (4-Hz click trains) that were presented at various moments during ongoing tACS (two synchronous 4-Hz alternating currents applied transcranially to the two cerebral hemispheres). We found that changes in the relative timing of acoustic and electric stimulation cause corresponding perceptual changes that oscillate predominantly at the 4-Hz frequency of the electric stimulation, which is consistent with previous results based on 10-Hz tACS. TACS at va...
While advances in magnetic resonance imaging (MRI) throughout the last decades have enabled the d... more While advances in magnetic resonance imaging (MRI) throughout the last decades have enabled the detailed anatomical and functional inspection of the human brain non-invasively, to date there is no consensus regarding the precise subdivision and topography of the areas forming the human auditory cortex. Here, we propose a topography of the human auditory areas based on insights on the anatomical and functional properties of human auditory areas as revealed by studies of cyto- and myelo-architecture and fMRI investigations at ultra-high magnetic field (7 Tesla). Importantly, we illustrate that-whereas a group-based approach to analyze functional (tonotopic) maps is appropriate to highlight the main tonotopic axis-the examination of tonotopic maps at single subject level is required to detail the topography of primary and non-primary areas that may be more variable across subjects. Furthermore, we show that considering multiple maps indicative of anatomical (i.e., myelination) as well ...
The transformation of acoustic signals into abstract perceptual representations is the essence of... more The transformation of acoustic signals into abstract perceptual representations is the essence of the efficient and goal-directed neural processing of sounds in complex natural environments. While the human and animal auditory system is perfectly equipped to process the spectrotemporal sound features, adequate sound identification and categorization require neural sound representations that are invariant to irrelevant stimulus parameters. Crucially, what is relevant and irrelevant is not necessarily intrinsic to the physical stimulus structure but needs to be learned over time, often through integration of information from other senses. This review discusses the main principles underlying categorical sound perception with a special focus on the role of learning and neural plasticity. We examine the role of different neural structures along the auditory processing pathway in the formation of abstract sound representations with respect to hierarchical as well as dynamic and distribute...
The Journal of neuroscience : the official journal of the Society for Neuroscience, Jan 10, 2012
Auditory cortical processing of complex meaningful sounds entails the transformation of sensory (... more Auditory cortical processing of complex meaningful sounds entails the transformation of sensory (tonotopic) representations of incoming acoustic waveforms into higher-level sound representations (e.g., their category). However, the precise neural mechanisms enabling such transformations remain largely unknown. In the present study, we use functional magnetic resonance imaging (fMRI) and natural sounds stimulation to examine these two levels of sound representation (and their relation) in the human auditory cortex. In a first experiment, we derive cortical maps of frequency preference (tonotopy) and selectivity (tuning width) by mathematical modeling of fMRI responses to natural sounds. The tuning width maps highlight a region of narrow tuning that follows the main axis of Heschl's gyrus and is flanked by regions of broader tuning. The narrowly tuned portion on Heschl's gyrus contains two mirror-symmetric frequency gradients, presumably defining two distinct primary auditory ...
The Journal of neuroscience : the official journal of the Society for Neuroscience, Jan 19, 2012
The formation of new sound categories is fundamental to everyday goal-directed behavior. Categori... more The formation of new sound categories is fundamental to everyday goal-directed behavior. Categorization requires the abstraction of discrete classes from continuous physical features as required by context and task. Electrophysiology in animals has shown that learning to categorize novel sounds alters their spatiotemporal neural representation at the level of early auditory cortex. However, functional magnetic resonance imaging (fMRI) studies so far did not yield insight into the effects of category learning on sound representations in human auditory cortex. This may be due to the use of overlearned speech-like categories and fMRI subtraction paradigms, leading to insufficient sensitivity to distinguish the responses to learning-induced, novel sound categories. Here, we used fMRI pattern analysis to investigate changes in human auditory cortical response patterns induced by category learning. We created complex novel sound categories and analyzed distributed activation patterns duri...
Uploads
Papers by Elia Formisano