Search

The ability to maintain a sequence of items in memory is a fundamental cognitive function. In the rodent hippocampus, the representation of sequentially organized spatial locations is reflected by the phase of action potentials relative to the theta oscillation (phase precession). We investigated whether the timing of neuronal activity relative to the theta brain oscillation also reflects sequence order in the medial temporal lobe of humans. We used a task in which human participants learned a fixed sequence of pictures and recorded single neuron and local field potential activity with implanted electrodes. We report that spikes for three consecutive items in the sequence (the preferred stimulus for each cell, as well as the stimuli immediately preceding and following it) were phase-locked at distinct phases of the theta oscillation. Consistent with phase precession, spikes were fired at progressively earlier phases as the sequence advanced. These findings generalize previous findings in the rodent hippocampus to the human temporal lobe and suggest that encoding stimulus information at distinct oscillatory phases may play a role in maintaining sequential order in memory., Previous work has shown that in rodents phase precession – the phase of action potentials relative to the theta oscillation – is associated with the representation of sequential locations. Here the authors demonstrate that phase precession also occurs in the human hippocampus using single neuron and LFP recordings.

Rapid decoding of emotional expressions is essential for social communication. Fast processing of facial expressions depends on the adequate (subcortical) processing of important global face cues in the low spatial frequency (LSF) ranges. However, children below 9 years of age extract fearful expression information from local details represented by high SF (HSF) image content. Our ERP study investigated at which developmental stage this ineffective HSF-driven processing is replaced by the proficient and rapid LSF-driven perception of fearful faces, in which adults are highly skilled. We examined behavioral and neural responses to high- and low-pass filtered faces with a fearful or neutral expression in groups of children on the verge of pre-adolescence (9-10 years), adolescents (14-15 years), and young adults (20-28 years). Our results suggest that the neural emotional face processing network has a protracted maturational course into adolescence, which is related to changes in SF processing. In mid-adolescence, increased sensitivity to emotional LSF cues is developed, which aids the fast and adequate processing of fearful expressions that might signal impending danger.

Face perception is characterized by configural processing, which depends on visual information in the low spatial frequency (LSF) ranges. However, it is unclear whether LSF content is equally important for face memory. The present study investigated how face information in the low and high SF range plays a role in the configural encoding of faces for short-term and long-term recall. Moreover, we examined how SF-dependent face memorization develops in female adolescence, by comparing children (9-10-year-olds), adolescents (12-13-year-olds and 15-16-year-olds), and young adults (21-32-year-olds). Results show that similar to face perception, delayed face recognition was consistently facilitated by LSF content. However, only adults were able to adequately employ configural LSF cues for short-term recall, analogous to the slow maturation of LSF-driven configural face perception reported by previous studies. Moreover, the insensitivity to face inversion of early adolescents revealed their inadequate use of configural face cues regardless of SF availability, corroborating previous reports on an adolescent "dip" in face recognition. Like face perception, face recognition has a protracted maturational course. In (female) adolescence, sensitivity to configural LSF cues is developed, which aids not only configural face perception but also face memorization.

Visual scenes are initially processed via segregated neural pathways dedicated to either of the two visual hemifields. Although higher-order visual areas are generally believed to utilize invariant object representations (abstracted away from features such as stimulus position), recent findings suggest they retain more spatial information than previously thought. Here, we assessed the nature of such higher-order object representations in human cortex using high-resolution fMRI at 7T, supported by corroborative 3T data. We show that multi-voxel activation patterns in both the contra- and ipsilateral hemisphere can be exploited to successfully classify the object category of unilaterally presented stimuli. Moreover, robustly identified rank order-based response profiles demonstrated a strong contralateral bias which frequently outweighed object category preferences. Finally, we contrasted different combinatorial operations to predict the responses during bilateral stimulation conditions based on responses to their constituent unilateral elements. Results favored a max operation predominantly reflecting the contralateral stimuli. The current findings extend previous work by showing that configuration-dependent modulations in higher-order visual cortex responses as observed in single unit activity have a counterpart in human neural population coding. They furthermore corroborate the emerging view that position coding is a fundamental functional characteristic of ventral visual stream processing.

How are tactile sensations in the breast represented in the female and male brain? Using ultra high-field 7 T MRI in ten females and ten males, we demonstrate that the representation of tactile breast information shows a somatotopic organization, with cortical magnification of the nipple. Furthermore, we show that the core representation of the breast is organized according to the specific nerve architecture that underlies breast sensation, where the medial and lateral sides of one breast are asymmetrically represented in bilateral primary somatosensory cortex. Finally, gradual selectivity signatures allude to a somatotopic organization of the breast area with overlapping, but distinctive, cortical representations of breast segments. Our univariate and multivariate analyses consistently showed similar somatosensory breast representations in males and females. The findings can guide future research on neuroplastic reorganization of the breast area, across reproductive life stages, and after breast surgery.

Face perception depends on a dynamic interplay of a "holistic" Interactive Feature Processing (IFP) and a Local Feature Processing (LFP) style. However, it is unclear whether features are processed locally before they are integrated into a holistic percept (Fine-to-Coarse strategy), or whether local feature processing occurs only after a holistic percept is established (Coarse-to-Fine strategy). The present Event-Related Potentials study investigates whether IFP precedes LFP (Coarse-to-Fine) or vice versa (Fine-to-Coarse). Participants matched target features within face pairs (here the eye region), in which distracter features (nose and mouth) called for the same or a different response (congruent and incongruent, respectively). Psychophysical results replicated previous findings. That is, dissimilar target features are locally processed (LFP), which minimizes interference from surrounding incongruent distracters. Conversely, an IFP mode is elicited when similar target features are embedded in dissimilar contexts. In IFP mode, incongruent distracters do interfere with the processing of similar target features, thereby deteriorating task performance. Face inversion, which preserves input properties but disrupts high-level face perception, annihilated these incongruency effects. Psychophysical observations were reflected at the neural level. The IFP and LFP modes of face perception elicited distinct time-courses in occipito-temporal cortex. IFP was affected by inversion as soon as 176 ms post-stimulus onset (coinciding with the N170 peak). In contrast, the first robust indications of LFP occurred 120 ms later, at 296 ms. Thus, the contribution of IFP to high-level face perception appears to temporally precede LFP. Moreover, results showed that the IFP and LFP modes did not only operate in distinct time intervals, but also in different brain areas: activity associated with the IFP mode was right-lateralized, whereas the LPF mode engaged the left hemisphere. In sum, interactive "holistic" encoding of facial features temporally precedes their local analysis. This agrees with models suggesting a Coarse-to-Fine strategy for face perception, in line with generic descriptions of visual perception in which global scene analysis precedes the examination of local details.

Paying selective attention to an audio frequency selectively enhances activity within primary auditory cortex (PAC) at the tonotopic site (frequency channel) representing that frequency. Animal PAC neurons achieve this 'frequency-specific attentional spotlight' by adapting their frequency tuning, yet comparable evidence in humans is scarce. Moreover, whether the spotlight operates in human midbrain is unknown. To address these issues, we studied the spectral tuning of frequency channels in human PAC and inferior colliculus (IC), using 7-T functional magnetic resonance imaging (FMRI) and frequency mapping, while participants focused on different frequency-specific sounds. We found that shifts in frequency-specific attention alter the response gain, but not tuning profile, of PAC frequency channels. The gain modulation was strongest in low-frequency channels and varied near-monotonically across the tonotopic axis, giving rise to the attentional spotlight. We observed less prominent, non-tonotopic spatial patterns of attentional modulation in IC. These results indicate that the frequency-specific attentional spotlight in human PAC as measured with FMRI arises primarily from tonotopic gain modulation, rather than adapted frequency tuning. Moreover, frequency-specific attentional modulation of afferent sound processing in human IC seems to be considerably weaker, suggesting that the spotlight diminishes toward this lower-order processing stage. Our study sheds light on how the human auditory pathway adapts to the different demands of selective hearing.

A sound of interest may be tracked amid other salient sounds by focusing attention on its characteristic features including its frequency. Functional magnetic resonance imaging findings have indicated that frequency representations in human primary auditory cortex (AC) contribute to this feat. However, attentional modulations were examined at relatively low spatial and spectral resolutions, and frequency-selective contributions outside the primary AC could not be established. To address these issues, we compared blood oxygenation level-dependent (BOLD) responses in the superior temporal cortex of human listeners while they identified single frequencies versus listened selectively for various frequencies within a multifrequency scene. Using best-frequency mapping, we observed that the detailed spatial layout of attention-induced BOLD response enhancements in primary AC follows the tonotopy of stimulus-driven frequency representations-analogous to the "spotlight" of attention enhancing visuospatial representations in retinotopic visual cortex. Moreover, using an algorithm trained to discriminate stimulus-driven frequency representations, we could successfully decode the focus of frequency-selective attention from listeners' BOLD response patterns in nonprimary AC. Our results indicate that the human brain facilitates selective listening to a frequency of interest in a scene by reinforcing the fine-grained activity pattern throughout the entire superior temporal cortex that would be evoked if that frequency was present alone.

Recognizing objects despite infinite variations in their appearance is a highly challenging computational task the visual system performs in a remarkably fast, accurate, and robust fashion. The complexity of the underlying mechanisms is reflected in the large proportion of cortical real-estate dedicated to visual processing, as well as in the difficulties encountered when trying to build models whose performance matches human proficiency. The articles in this Research Topic provide an overview of recent advances in our understanding of the neural mechanisms underlying visual object perception, focusing on integrative approaches which encompass both computational and empirical work. Given the vast expanse of topics covered in the discipline of computational visual neuroscience, it is impossible to provide a comprehensive overview of the field's status-quo. Instead, the presented papers highlight interesting extensions to existing models and novel insights into computational principles and their neural underpinnings. Contributions could be coarsely subdivided into three different sections: Two papers focused on implementing biologically-valid learning rules and heuristics in well-established neural models of the visual pathway (i.e., “VisNet” and “HMAX”) to improve flexible object recognition. Three other studies investigated the role of sparseness, selectivity, and correlation in optimizing neural coding of object features. Finally, another set of contributions focused on integrating computational vision models and human brain responses to gain more insights in the computational mechanisms underlying neural object representations.

Recent studies have revealed a strong relationship between visual working memory and selective attention, such that attention is biased by what is currently on our mind. However, other data show that not all memorized items influence the deployment of attention, thus calling for a distinction within working memory: whereas active memory items function as an attentional template and directly affect perception, other, accessory items do not. We review recent evidence that items compete for the status of 'attentional template' that contains only one object at a time. Neurophysiological results provide insight into these different memory states by revealing a more intricate organization of working memory than was previously thought. © 2011 Elsevier Ltd.

Computational neuromodeling may help to further our understanding of how empirical neuroimaging findings are generated by underlying neural mechanisms. Here, we used a simple computational model that simulates early visual processing of brightness changes in a dynamic, illusory display. The model accurately predicted illusory brightness changes in a grey area of constant luminance induced by (and in anti-phase to) luminance changes in its surroundings. Moreover, we were able to directly compare these predictions with recently observed fMRI results on the same brightness illusion by projecting predicted activity from our model onto empirically investigated brain regions. This new approach in which generated network activity and measured neuroimaging data are interfaced in a common representational "brain space" can contribute to the integration of computational and experimental neuroscience.

If we search for an item, a representation of this item in our working memory guides attention to matching items in the visual scene. We can hold multiple items in working memory. Do all these items guide attention in parallel? We asked participants to detect a target object in a stream of objects while they maintained a second item in memory for a subsequent task. On some trials, we presented this memory item as a distractor in the stream. Subjects did not confuse these memory items with the search target, as the false alarm rate on trials where the memory item was presented in the stream was comparable to that on trials with only regular distractors. However, a comparable performance does not exclude that the memory items are processed differently from normal distractors. We therefore recorded event-related potentials (ERPs) evoked by search targets, memory items, and regular distractors. As expected, ERPs evoked by search targets differed from those evoked by distractors. Search targets elicited an occipital selection negativity and a frontal selection positivity indexing selective attention, whereas the P3b component, which reflects the matching of sensory events to memory representations, was enhanced for targets compared to distractors. Remarkably, the ERPs evoked by memory items were indistinguishable from the ERPs evoked by normal distractors. This implies that the search target has a special status in working memory that is not shared by the other items. These other, “accessory” items do not guide attention and are excluded from the matching process.

Here we report the first quantitative analysis of spiking activity in human early visual cortex. We recorded multi-unit activity from two electrodes in area V2/V3 of a human patient implanted with depth electrodes as part of her treatment for epilepsy. We observed well-localized multi-unit receptive fields with tunings for contrast, orientation, spatial frequency, and size, similar to those reported in the macaque. We also observed pronounced gamma oscillations in the local-field potential that could be used to estimate the underlying spiking response properties. Spiking responses were modulated by visual context and attention. We observed orientation-tuned surround suppression: responses were suppressed by image regions with a uniform orientation and enhanced by orientation contrast. Additionally, responses were enhanced on regions that perceptually segregated from the background, indicating that neurons in the human visual cortex are sensitive to figure-ground structure. Spiking responses were also modulated by object-based attention. When the patient mentally traced a curve through the neurons’ receptive fields, the accompanying shift of attention enhanced neuronal activity. These results demonstrate that the tuning properties of cells in the human early visual cortex are similar to those in the macaque and that responses can be modulated by both contextual factors and behavioral relevance. Our results, therefore, imply that the macaque visual system is an excellent model for the human visual cortex., Quantitative analysis of spiking activity of neurons in area V2/V3 of the human visual cortex shows remarkable similarities to the response properties of neurons in the early visual cortex of the macaque monkey, justifying extrapolation between species., Author Summary Our knowledge of the function of the early visual cortex is based largely on recordings of spiking activity from neurons in animal models, in particular the macaque monkey. Indirect measurements of neuronal activity in the human visual cortex have suggested many similarities with the macaque visual cortex, but to date there have been no quantitative analyses of spiking data in the human early visual cortex. In this paper, we report spiking data recorded from the early visual cortex of a patient who was implanted with depth electrodes as part of her treatment for epilepsy. We were able to verify that human visual neurons have response properties similar to macaque neurons, including the size of their receptive fields and the presence of orientation tuning. We also found that the responses of human visual neurons are modulated by the visual context and by shifts of attention in a virtually identical manner to neurons in the macaque. This study, therefore, shows that the macaque visual system provides an excellent model for human visual cortical processing.

Face perception in adults depends on skilled processing of interattribute distances ('configural' processing), which is disrupted for faces presented in inverted orientation (face inversion effect or FIE). Children are not proficient in configural processing, and this might relate to an underlying immaturity to use facial information in low spatial frequency (SF) ranges, which capture the coarse information needed for configural processing. We hypothesized that during adolescence a shift from use of high to low SF information takes place. Therefore, we studied the influence of SF content on neural face processing in groups of children (9-10 years), adolescents (14-15 years) and young adults (21-29 years) by measuring event-related potentials (ERPs) to upright and inverted faces which varied in SF content. Results revealed that children show a neural FIE in early processing stages (i.e. P1; generated in early visual areas), suggesting a superficial, global facial analysis. In contrast, ERPs of adults revealed an FIE at later processing stages (i.e. N170; generated in face-selective, higher visual areas). Interestingly, adolescents showed FIEs in both processing stages, suggesting a hybrid developmental stage. Furthermore, adolescents and adults showed FIEs for stimuli containing low SF information, whereas such effects were driven by both low and high SF information in children. These results indicate that face processing has a protracted maturational course into adolescence, and is dependent on changes in SF processing. During adolescence, sensitivity to configural cues is developed, which aids the fast and holistic processing that is so special for faces.

Peters JC, Reithler J, Schuhmann T, de Graaf T, Uludag. K, Goebel R, Sack AT. On the feasibility of concurrent human TMS-EEG-fMRI measurements. J Neurophysiol 109: 1214-1227, 2013. First published December 5, 2012; doi:10.1152/jn.00071.2012.-Simultaneously combining the complementary assets of EEG, functional MRI (fMRI), and transcranial magnetic stimulation (TMS) within one experimental session provides synergetic results, offering insights into brain function that go beyond the scope of each method when used in isolation. The steady increase of concurrent EEG-fMRI, TMS-EEG, and TMS-fMRI studies further underlines the added value of such multimodal imaging approaches. Whereas concurrent EEG-fMRI enables monitoring of brain-wide network dynamics with high temporal and spatial resolution, the combination with TMS provides insights in causal interactions within these networks. Thus the simultaneous use of all three methods would allow studying fast, spatially accurate, and distributed causal interactions in the perturbed system and its functional relevance for intact behavior. Concurrent EEG-fMRI, TMS-EEG, and TMS-fMRI experiments are already technically challenging, and the three-way combination of TMS-EEG-fMRI might yield additional difficulties in terms of hardware strain or signal quality. The present study explored the feasibility of concurrent TMS-EEG-fMRI studies by performing safety and quality assurance tests based on phantom and human data combining existing commercially available hardware. Results revealed that combined TMS-EEG-fMRI measurements were technically feasible, safe in terms of induced temperature changes, allowed functional MRI acquisition with comparable image quality as during concurrent EEG-fMRI or TMS-fMRI, and provided artifact-free EEG before and from 300 ms after TMS pulse application. Based on these empirical findings, we discuss the conceptual benefits of this novel complementary approach to investigate the working human brain and list a number of precautions and caveats to be heeded when setting up such multimodal imaging facilities with current hardware.

During visual search, the working memory (WM) representation of the search target guides attention to matching items in the visual scene. However, we can hold multiple items in WM. Do all these items guide attention at the same time? Using a new functional magnetic resonance imaging visual search paradigm, we found that items in WM can attain two different states that influence activity in extrastriate visual cortex in opposite directions: whereas the target item in WM enhanced processing of matching visual input, other "accessory" items in memory suppressed activity. These results imply that the representation of task-relevant and (currently) task-irrelevant representations in WM differs, revealing new insights into the organization of human visual WM. The suppressive influence of irrelevant WM items may complement the attention-guiding influence of task-relevant WM items, helping us to focus on task-relevant information without getting distracted by irrelevant memory content. © 2012 the authors.

Since its introduction in the 1980s, Transcranial Magnetic Stimulation (TMS) has proven to be a versatile method to non-invasively study human brain function by reversibly altering ongoing neural processing. In addition, TMS has been explored as a therapeutic intervention in a number of neurological and neuropsychiatric conditions. However, our understanding of TMS-induced changes in neural activity patterns is still rather limited, particularly when it comes to changes in neural network dynamics beyond the cortical site directly targeted by TMS. In order to monitor both its local and remote neurophysiological effects, TMS has been combined with complementary neuroimaging methods that allow additional insights into how observed TMS effects at the behavioral level can be interpreted by taking into account the full scale of its impact throughout the brain. The current review provides a comprehensive overview of the existing multimodal TMS literature, covering studies in which TMS was combined with one of the three main neuroimaging modalities, namely Electroencephalography, Positron Emission Tomography, and functional Magnetic Resonance Imaging. Besides constituting a reflection of the status quo in this exciting multidisciplinary research field, this review additionally reveals both convergent and divergent observations across modalities that await corroboration or resolution, thereby further guiding ongoing basic research and providing useful constraints to optimize future clinical applications.

Recent evidence suggests that both spatiotemporally distinct and overlapping brain regions are involved in bottom-up- and top-down-driven attentional processing. However, existing studies are based on a variety of different approaches, including electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), raising the question of how EEG and fMRI findings in this field are related to each other. The present study aimed at disentangling common from specific regions underlying bottom-up novelty-processing and top-down target-processing. Simultaneous EEG and fMRI recordings were employed to investigate how fMRI-identified brain regions contribute to event-related potential (ERP) signatures of novelty- and target-processing. Fourteen subjects performed a modified novelty oddball task in which either rare tones or novel sounds served as targets in different blocks, allowing us to separate novelty-related from mere distractor-related effects. ERP signatures of novelty- and target-processing could be identified, confirming previous research based on recordings outside the scanner. fMRI analyses revealed that, despite considerable overlap of regions activated during novelty- and target-processing, bilateral superior temporal and right inferior frontal areas showed pronounced activation related to novelty-processing. fMRI-informed ERP dipole seeding was used to integrate both signals. The source modeling results further implicated temporal and inferior frontal sources in novelty-processing. Target-related fMRI activation on the other hand was confirmed in a network comprising distributed frontoparietal regions as well as bilateral caudate nucleus and cerebellum. Most regions identified by fMRI showed a contribution to target-related ERP signatures. This pattern of findings underscores the potential of simultaneous EEG/fMRI recordings for the spatiotemporal characterization of target- and novelty-processing.

Accompanying source data for the publication entitled “Concurrent human TMS-EEG-fMRI enables monitoring of oscillatory brain state-dependent gating of cortico-subcortical network activity” (Peters, Reithler et al., 2020, Communications Biology). In all filenames, P1 and P2 indicate (“high-activators”) participant 1 and 2, respectively. Dataset 1 (fig1_fMRI_data.rar; 5 files) contains the fMRI data underlying Fig1: 'P2_ADNI_IIHC_ACPC.vmr': anatomical MRI file (BrainVoyager format) on which the *.vmp files can be superimposed. ‘P2_FingerTap_vs_AudioOnly.vmp’: statistical map fMRI file (BrainVoyager format) containing the GLM contrast between activity in the Motor Execution task and the control task (only auditory cues but no motor activity). This statistical map contains the whole brain image, of which a transversal slice is shown in Fig 1a. 'P2_FTvsBsln_ROIrPMd.dat': text file containing the average time courses of Motor Execution-events (FingerTapping, FT) in rPMd, shown in inset of Fig1a. Note that the header contains plotting information (BrainVoyager format). The / section contains the means (column 1) and standard errors (column 2) per datapoint for the Motor Execution task (section 1 "Curve 1: FingerTap") and the control task (section2 "Curve 2: Audio"). 'P2_R1-5_allTMS_vs_bsln.vmp': statistical map fMRI file (BrainVoyager format) containing the GLM contrast between activity in TMS-events and baseline (rest). This statistical map contains the whole brain image, of which a transversal slice is shown in Fig 1c. 'P2_AllTMSvsBsln_ROIrPMd.dat': text file containing the average time courses of TMS-events in rPMd, shown in inset of Fig1c. Data format similar to *.dat file above. Dataset 2 (fig2_fMRI_data.rar; 36 files) contains the fMRI data underlying Fig2: *.vmr': anatomical MRI file (BrainVoyager format), which is inhomogeneity corrected (abbreviated in filename as “IIHC”) and transformed to ACPC space (in filename: “ACPC”). Other abbreviations in the filename indicate the following: ‘subcortical_segmentation’: segmentation of the subcortical ROIs ‘LH’: left hemisphere ‘RH’: right hemisphere *.srf/.svp': Smoothed mesh reconstructions (anatomical MRI file; BrainVoyager format) of the entire cortex as well as reconstructions of the cortical and subcortical Regions-of-Interest (ROIs). Each *.srf file contains a mesh surface reconstruction and is accompanied by a *.svp file with the same filename. The *.svp contains the “surface viewpoint” settings (BrainVoyager format), which position the surface and lightning conditions to recreate Fig 2. However, note that the *.srf file can also be used without *.svp files. Filename conventions are identical to vmr files. Additional abbreviations in the filename indicate the following: (sub)cortical_ME_ROIs: (sub)cortical Motor Execution (ME) ROIs (sub)cortical_TMS_ROIs: (sub)cortical TMS- responsive (TMS) ROIs Dataset 3 (Fig3and4_Matlab_data.rar; 5 files) contains the matlab data and corresponding code (related to the EEG-informed fMRI analyses) to generate Fig3 and Fig4: 'fMRIactivity_AlphaClasses.mat': matlab file containing the 5-dimensional array ‘Alpha_TrialsxPowerClassxROITypexROIsxSubj’. The 5 dimensions represent: 1) TMS-evoked BOLD responses (indexed by their average beta value) in 40 trials, 2) weak and strong power class, 3) Motor Execution and TMS-responsive ROIs, 4) cortical and subcortical ROIs ('rPMd','lPMd','rM1','SMA','rCN','rPut','rThal','lThal','lPut','lCN'), 5) Participants. 'Plot_Paper_Fig3.m': matlab code textfile to generate Figure 3 which shows that TMS-induced BOLD changes in cortical ROIs depend on pre-TMS alpha power. See comments in m-file for details. By running the code, a figure is created and saved as ‘Fig3.fig’. 'Plot_Paper_Fig4.m': matlab code textfile to generate Figure 4 which shows that also in subcortical ROIs, TMS-induced BOLD changes depend on pre-TMS alpha power. See comments in m-file for details. By running the code, a figure is created and saved as ‘Fig4.fig’. ‘Fig3.fig’: Figure resulting from running script 'Plot_Paper_Fig3.m'. ‘Fig4.fig’: Figure resulting from running script 'Plot_Paper_Fig4.m'., v2: Barplot_fMRIrespperCorticalROI_fig3.m and Barplot_fMRIrespperSubCorticalROI_fig4.m have nearly the same functionality as Plot_Paper_Fig3.m and Plot_Paper_Fig4.m respectively but offer an alternative way to visualize the single-trial data