Posterior Inferior Temporal Cortex Research Articles

Hierarchical organization of the human ventral visual streams revealed with magnetoencephalography.

The hierarchical organization between 25 ventral stream visual cortical regions and 180 cortical regions was measured with magnetoencephalography using the Human Connectome Project Multimodal Parcellation atlas in 83 Human Connectome Project participants performing a visual memory task. The aim was to reveal the hierarchical organization using a whole-brain model based on generative effective connectivity with this fast neuroimaging method. V1-V4 formed a first group of interconnected regions. Especially V4 had connectivity to a ventrolateral visual stream: V8, the fusiform face cortex, and posterior inferior temporal cortex PIT. These regions in turn had effectivity connectivity to inferior temporal cortex visual regions TE2p and TE1p. TE2p and TE1p then have connectivity to anterior temporal lobe regions TE1a, TE1m, TE2a, and TGv, which are multimodal. In a ventromedial visual stream, V1-V4 connect to ventromedial regions VMV1-3 and VVC. VMV1-3 and VVC connect to the medial parahippocampal gyrus PHA1-3, which, with the VMV regions, include the parahippocampal scene area. The medial parahippocampal PHA1-3 regions have connectivity to the hippocampal system regions the perirhinal cortex, entorhinal cortex, and hippocampus. These effective connectivities of two ventral visual cortical streams measured with magnetoencephalography provide support to the hierarchical organization of brain systems measured with fMRI, and new evidence on directionality.

Limited Pairings of Electrical Micro-stimulation of the Ventral Tegmental Area and a Visual Stimulus Enhance Visual Cortical Responses.

Previous studies demonstrated that pairing a visual stimulus and electrical micro-stimulation of the ventral tegmental area (VTA-EM) for multiple days is sufficient to induce visual cortical plasticity and changes perception. However, a brief epoch of VTA-EM-stimulus pairing within a single day has been shown to result in a behavioral preference for the paired stimulus. Here, we investigated whether a brief single-day session of VTA-EM-stimulus pairings is sufficient to induce changes in visual cortical responses. We examined macaque posterior inferior temporal (PIT) cortex because previous studies demonstrated response changes after VTA-EM stimulus pairing in that area. Multi-unit recordings in PIT were interleaved with VTA-EM-stimulus pairing epochs. During the short VTA-EM-stimulus pairing epochs (60 pairings), one image (fractal) was paired with VTA-EM (STIM) whereas another, unpaired fractal was presented as control. Two other fractals (dummies) were presented only during the recordings. The difference in response between the STIM and control fractals already increased after the first VTA-EM-stimulus pairing epoch, reflecting a relative increase of the response to the STIM fractal. However, the response to the STIM fractal did not increase further with more VTA-EM-stimulus pairing epochs. The relative increase in firing rate for the paired fractal was present early in the response, in line with a local/ bottom-up origin. These effects were absent when comparing the responses to the dummies pre- and post-VTA-EM. This study shows that pairing a visual image and VTA-EM in a brief single-day session is sufficient to increase the response for the paired image in macaque PIT.

Classification of 18F-Flutemetamol scans in cognitively normal older adults using machine learning trained with neuropathology as ground truth

PurposeEnd-of-life studies have validated the binary visual reads of 18F-labeled amyloid PET tracers as an accurate tool for the presence or absence of increased neuritic amyloid plaque density. In this study, the performance of a support vector machine (SVM)-based classifier will be tested against pathological ground truths and its performance determined in cognitively healthy older adults.MethodsWe applied SVM with a linear kernel to an 18F-Flutemetamol end-of-life dataset to determine the regions with the highest feature weights in a data-driven manner and to compare between two different pathological ground truths: based on neuritic amyloid plaque density or on amyloid phases, respectively. We also trained and tested classifiers based on the 10% voxels with the highest amplitudes of feature weights for each of the two neuropathological ground truths. Next, we tested the classifiers’ diagnostic performance in the asymptomatic Alzheimer’s disease (AD) phase, a phase of interest for future drug development, in an independent dataset of cognitively intact older adults, the Flemish Prevent AD Cohort-KU Leuven (F-PACK). A regression analysis was conducted between the Centiloid (CL) value in a composite volume of interest (VOI), as index for amyloid load, and the distance to the hyperplane for each of the two classifiers, based on the two pathological ground truths. A receiver operating characteristic analysis was also performed to determine the CL threshold that optimally discriminates between neuritic amyloid plaque positivity versus negativity, or amyloid phase positivity versus negativity, within F-PACK.ResultsThe classifiers yielded adequate specificity and sensitivity within the end-of-life dataset (neuritic amyloid plaque density classifier: specificity of 90.2% and sensitivity of 83.7%; amyloid phase classifier: specificity of 98.4% and sensitivity of 84.0%). The regions with the highest feature weights corresponded to precuneus, caudate, anteromedial prefrontal, and also posterior inferior temporal and inferior parietal cortex. In the cognitively normal cohort, the correlation coefficient between CL and distance to the hyperplane was −0.66 for the classifier trained with neuritic amyloid plaque density, and −0.88 for the classifier trained with amyloid phases. This difference was significant. The optimal CL cut-off for discriminating positive versus negative scans was CL = 48–51 for the different classifiers (area under the curve (AUC) = 99.9%), except for the classifier trained with amyloid phases and based on the 10% voxels with highest feature weights. There the cut-off was CL = 26 (AUC = 99.5%), which closely matched the CL threshold for discriminating phases 0–2 from 3–5 based on the end-of-life dataset and the neuropathological ground truth.DiscussionAmong a set of neuropathologically validated classifiers trained with end-of-life cases, transfer to a cognitively normal population works best for a classifier trained with amyloid phases and using only voxels with the highest amplitudes of feature weights.

Microglia activation predicts tau positivity beyond Aβ in Alzheimer’s disease

AbstractBackgroundDeposition of amyloid‐beta (Aβ) plaques and hyperphosphorylated tau are known hallmarks of Alzheimer’s disease (AD). In addition, neuroinflammation or microglia activation plays a role in Alzheimer’s pathophysiology and may be a potential driver of abnormal tau deposition. This study demonstrated the important brain regions where microglia activation, in addition to Aβ, is driving tau positivity in AD.Method120 participants from the TRIAD cohort underwent 18F‐AZD4694 amyloid‐PET, 18F‐MK620 tau‐PET, and 11C‐PBR28 neuroinflammation‐PET. All images were normalized to the ADNI template and quantified as SUVR in 35 regions‐of‐interest using cerebellar gray as the reference region. ANCOVA was used to assess the differences in levels of microglia activation between tau‐positive (T+; n=38) vs. tau‐negative (T‐; n=82), corrected for age, sex, APOE‐e4, education, and global Aβ. Tau status was based on both visual rating with elevated uptake in Braak1and2 and quantitative cut‐off of 1.22. In addition, step‐wise logistic regression was conducted to predict T+ in three steps: 1) the covariates, i.e. age, sex, APOEε4, and education, 2) covariates + global Aβ, and 3) covariates + global Aβ + activated microglia in each of the 35 ROIs, corrected for multiple comparisons using FDR. Our prediction model was trained based on a randomly selected 70%/30% training/test set. In order to investigate the stability of our model, this procedure was repeated 500 times.ResultLevels of microglia activation were significantly increased in T+ compared to T‐ in the posterior cingulate (p=0.0001), middle (p=0.02) and inferior (p=0.0005) temporal, fusiform (p=0.0004), and orbitofrontal cortex (p=0.005). Based on logistic regression and a likelihood‐ratio test between each step, we found that the ‘covariates + global Aβ model’ performed significantly better in predicting T+ than the ‘covariates‐only’ model (χ2(1)=72.64, p<0.0001). In the 3‐step model, the addition of activated microglia showed a significantly improvement of the model’s performance to predict T+, particularly the activated microglia in the hippocampus (p=0.001), middle (p=0.006) and inferior (p=0.001) temporal, and fusiform (p=0.001) cortex. Receiver operating characteristic curves (ROC) and AUCs are shown in Fig 1.ConclusionOur study demonstrated that activated microglia in the Braak2 to Braak4 regions play an important role in predicting tau positivity in addition to Aβ.

Microglia activation predicts tau positivity beyond Aβ in Alzheimer’s disease

AbstractBackgroundDeposition of amyloid‐beta (Aβ) plaques and hyperphosphorylated tau are known hallmarks of Alzheimer’s disease (AD). In addition, neuroinflammation or microglia activation plays a role in AD pathophysiology and may be a potential driver of abnormal tau deposition. This study demonstrated the important brain regions where microglia activation, in addition to Aβ, is driving tau positivity in AD.Method120 participants from the TRIAD cohort underwent 18F‐AZD4694 amyloid‐PET, 18F‐MK620 tau‐PET, and 11C‐PBR28 neuroinflammation‐PET. All images were normalized to the ADNI template and quantified as SUVR in 35 regions‐of‐interest using cerebellar gray as the reference region. ANCOVA was used to assess the differences in levels of microglia activation between tau‐positive (T+; n=38) vs. tau‐negative (T‐; n=82), corrected for age, sex, APOE‐e4, education, and global Aβ. Tau status was based on both visual rating with elevated uptake in Braak1and2 and quantitative cut‐off of 1.22. In addition, step‐wise logistic regression was conducted to predict T+ in three steps: 1) the covariates, i.e. age, sex, APOEε4, and education, 2) covariates + global Aβ, and 3) covariates + global Aβ + activated microglia in each of the 35 ROIs, corrected for multiple comparisons using FDR. Our prediction model was trained based on a randomly selected 70%/30% training/test set. In order to investigate the stability of our model, this procedure was repeated 500 times.ResultLevels of microglia activation were significantly increased in T+ compared to T‐ in the posterior cingulate (p=0.0001), middle (p=0.02) and inferior (p=0.0005) temporal, fusiform (p=0.0004), and orbitofrontal cortex (p=0.005). Based on logistic regression and a likelihood‐ratio test between each step, we found that the ‘covariates + global Aβ model’ performed significantly better in predicting T+ than the ‘covariates‐only’ model (χ2(1)=72.64, p<0.0001). In the 3‐step model, the addition of activated microglia showed a significant improvement of the model’s performance to predict T+, particularly the activated microglia in the hippocampus (p=0.001), middle (p=0.006) and inferior (p=0.001) temporal, and fusiform (p=0.001) cortex. Receiver operating characteristic curves (ROC) and AUCs are shown in Fig 1.ConclusionOur study demonstrated that activated microglia in the Braak2 to Braak4 regions play an important role in predicting tau positivity in addition to Aβ.

Stimulation of the ventral tegmental area induces visual cortical plasticity at the neuronal level.

fMRI studies have shown that pairing a task-irrelevant visual feature with electrical micro-stimulation of the ventral tegmental area (VTA-EM) is sufficient to increase the sensory cortical representation of the paired feature and to improve perceptual performance. However, since fMRI provides an indirect measure of neural activity, the neural response changes underlying the fMRI activations are unknown. Here, we pair a task-irrelevant grating orientation with VTA-EM while attention is directed to a difficult orthogonal task. We examine the changes in neural response properties in macaques by recording spiking activity in the posterior inferior temporal cortex, the locus of fMRI-defined plasticity in previous studies. We observe a relative increase in mean spike rate and preference for the VTA-EM paired orientation compared to an unpaired orientation, which is unrelated to attention. These results demonstrate that VTA-EM-stimulus pairing is sufficient to induce sensory cortical plasticity at the spiking level in nonhuman primates.

Differences of apathy perfusion correlates between Alzheimer’s disease and frontotemporal dementia. A 99mTc-HMPAO SPECT study with automated Brodmann areas analysis

Objectives To explore differences of apathy perfusion correlates between Alzheimer’s disease (AD) and Frontotemporal dementia (FTD) using perfusion SPECT. Methods We studied 75 FTD and 66 AD patients. We evaluated apathy using Neuropsychiatric Inventory (NPI). We compared perfusion of BAs on left (L) and right (R) hemisphere in AD and FTD. Results Apathy in AD was significantly and negatively correlated with dorsolateral prefrontal cortex bilaterally, right anterior prefrontal cortex, inferior frontal cortex bilaterally, especially on the right, orbital part of inferior frontal gyrus bilaterally, left dorsal anterior cingulate cortex, right primary and secondary visual cortex, and with bilateral anterior and dorsolateral prefrontal cortex, inferior frontal cortex and orbital part of inferior frontal gyrus, bilaterally, bilateral anterior -ventral and dorsal- cingulate cortex, left posterior ventral cingulate cortex, right inferior, middle and anterior temporal gyri, entorhinal and parahippocampal cortex in FTD. Conclusions Significant overlapping of apathy perfusion correlates between AD and FTD is seen in frontal areas and anterior cingulate. Right occipital cortex is also involved in AD, while right temporal cortex and left posterior cingulate are involved in FTD. Nuclear imaging could be a useful biomarker for revealing apathy underlying mechanisms, resulting in directed treatments. KEYPOINTS Underlying neural networks and clinical manifestation of apathy may differ between AD and FTD. Apathy in AD is correlated with hypoperfusion in bilateral frontal areas, more prominent on the right, left anterior cingulate and right occipital cortex. Apathy in FTD is correlated with hypoperfusion in bilateral frontal areas, bilateral anterior cingulate, left posterior cingulate and right temporal cortex. Brain perfusion SPECT with automated BAs analysis and comparison with normal healthy subjects may provide significant information for apathy mechanisms in neurodegenerative disorders, affecting patients’ treatment.

Selective impairment of On-reading (Chinese-style pronunciation) in alexia with agraphia for kanji due to subcortical hemorrhage in the left posterior middle temporal gyrus

ABSTRACT We report a patient with alexia with agraphia for kanji after hemorrhage in the left posterior middle temporal gyrus. The results of single-character kanji reading and two-character on- (Chinese-style pronunciation), kun- (native Japanese pronunciation), and Jukujikun (irregular kun-) reading word tests revealed that the patient could not read kanji characters with on-reading but read the characters with kun-reading. We consider that this on-reading alexia was caused by disconnection between the posterior inferior temporal cortex (orthographic lexicon) and the posterior superior temporal gyrus (phonological lexicon), and preserved kun- and Jukujikun-reading was realized by bypassing the orthography-to-phonology route by the semantic route.

Tau PET Distributional Pattern in AD Patients with Visuospatial Dysfunction.

Visuospatial dysfunction is one predominant symptom in many atypical Alzheimer's disease (AD) patients, however, until now its neural correlates still remain unclear. For the accumulation of intracellular hyperphosphorylated tau proteins is a major pathogenic factor in neurodegeneration of AD, the distributional pattern of tau could highlight the affected brain regions associated with specific cognitive deficits. We investigated the brain regions particularly affected by tau accumulation in patients with visuospatial dysfunction to explore its neural correlates. Using 18F-AV-1451 tau positron emission tomography (PET), voxel-wise two-sample t-tests were performed between AD patients with obvious visuospatial dysfunction (VS-AD) and cognitively normal subjects, AD patients with little-to-no visuospatial dysfunction (non VS-AD) and cognitively normal subjects, respectively. Results showed increased tau accumulations mainly located in occipitoparietal cortex, posterior cingulate cortex, precuneus, inferior and medial temporal cortex in VS-AD patients, while increased tau accumulations mainly occurred in the inferior and medial temporal cortex in non VS-AD patients. These findings suggested that occipitoparietal cortex, posterior cingulate cortex and precuneus, which were particularly affected by increased tau accumulation in VS-AD patients, may associate with visuospatial dysfunction of AD.

Linguistic networks associated with lexical, semantic and syntactic predictability in reading: A fixation-related fMRI study

The ability to make predictions is thought to facilitate language processing. During language comprehension such predictions appear to occur at multiple levels of linguistic representations (i.e. semantic, syntactic and lexical). The neural mechanisms that define the network sensitive to linguistic predictability have yet to be adequately defined. The purpose of the present study was to explore the neural network underlying predictability during the normal reading of connected text. Predictability values for different linguistic information were obtained from a pre-existing text corpus. Forty-one subjects underwent simultaneous eye-tracking and fMRI scans while reading these select paragraphs. Lexical, semantic, and syntactic predictability measures were then correlated with functional activation associated with fixation onset on the individual words. Activation patterns showed both positive and negative correlations to lexical, semantic, and syntactic predictabilities. Conjunction analysis revealed regions specific to or shared between each type of predictability. The regions associated with the different predictability measures were largely separate. Results suggest that most linguistic predictions are graded in nature, activating components of the existing language system. A number of regions were also found to be uniquely associated with full lexical predictability, most notably the anterior temporal lobe and the inferior posterior temporal cortex.

Kanji (Morphogram) and Kana (Phonogram) Problem in Japanese Alexia and Agraphia.

The kanji and kana (or kanji vs. kana) problem in the Japanese language denotes the dissociation between kanji (morphograms) and kana (phonograms) in reading/comprehension and writing. Since paragraphia of kana in a patient with amyotrophic lateral sclerosis was first reported in 1893, kanji-kana dissociation has been the central topic in Japanese aphasiology. Recent advancements in lesion-to-symptom analyses and functional imaging studies have identified some areas whose damage causes dissociative disturbances of reading or writing between kanji and kana. That is, (1) angular alexia with agraphia causes kanji agraphia; alexia of kana with an angular gyrus lesion is the result of a damage to the middle occipital gyrus; (2) alexia with agraphia for kanji is caused by a posterior inferior temporal cortex (mid-fusiform/inferior temporal gyri; visual word form area) lesion, whereas pure agraphia for kanji is caused by a posterior middle temporal gyrus lesion; and (3) pure alexia, particularly for kanji, results from a mid-fusiform gyrus lesion (Brodmann's Area [BA] 37), whereas pure alexia for kana results from a posterior fusiform/inferior occipital gyri lesion (BA 18/19).

Spatiotemporal Analysis of Event-related Current Density Reveals Dissociable Effects of Arousal and Valence on Emotional Picture Processing.

BackgroundThe processing of emotional visual stimulation involves the processing of emotional and visuoperceptual information. It is not completely revealed how the valence and arousal affect these two aspects. The objective was to investigate the effects of valence and arousal on spatiotemporal characteristics of cortical information processing using distributed source imaging of event-related current density (ERCD).MethodsElectroencephalograms (64 channels) were recorded from 19 healthy men while presenting affective pictures. Distributed source localization analysis was adopted to obtain the spatiotemporal pattern of ERCD on cortical surface in response to emotional visual stimulation. A nonparametric cluster-based permutation test was used to find meaningful time and space without prior knowledge.ResultsSignificant changes of ERCD in 400–800 ms among positive, negative, and neutral emotional conditions were found in left posterior cingulate cortex (PCC) and right inferior temporal cortex (ITC). In the PCC, the stimuli with higher arousal levels showed more negative ERCD than neutral stimuli. In the ITC, the ERCD for negative stimuli was significantly more negative than those of positive and neutral ones.ConclusionArousal and valence had strong influence on memory encoding and visual analysis at late period. The location and time showing significant change in neural activity according to arousal and valence would provide valuable information for understanding the changes of cortical function by neuropsychiatric disorders.

Associations of brain entropy (BEN) to cerebral blood flow and fractional amplitude of low-frequency fluctuations in the resting brain.

Entropy is a fundamental trait of human brain. Using fMRI-based brain entropy (BEN) mapping, interesting findings have been increasingly revealed in normal brain and neuropsychiatric disorders. As BEN is still relatively new, an often-raised question is how much new information can this measure tell about the brain compared to other more established brain activity measures. The study aimed to address that question by examining the relationship between BEN and cerebral blood flow (CBF) and the fractional amplitude of low-frequency fluctuations (fALFF), two widely used resting state brain state measures. fMRI data acquired from a large cohort of normal subjects were used to calculate the three metrics; inter-modality associations were assessed at each voxel through the Pearson correlation analysis. A moderate to high positive BEN-CBF and BEN-fALFF correlations were found in orbito-frontal cortex (OFC) and posterior inferior temporal cortex (ITC); Strong negative BEN-fALFF correlations were found in visual cortex (VC), anterior ITC, striatum, motor network, precuneus, and lateral parietal cortex. Positive CBF-fALFF correlations were found in medial OFC (MOFC), medial prefrontal cortex (MPFC), left angular gyrus, and left precuneus. Significant gender effects were observed for all three metrics and their correlations. Our data clearly demonstrated that BEN provides unique information that cannot be revealed by CBF and fALFF.

Brain Mechanisms of Arithmetic: A Crucial Role for Ventral Temporal Cortex.

Elementary arithmetic requires a complex interplay between several brain regions. The classical view, arising from fMRI, is that the intraparietal sulcus (IPS) and the superior parietal lobe (SPL) are the main hubs for arithmetic calculations. However, recent studies using intracranial electroencephalography have discovered a specific site, within the posterior inferior temporal cortex (pITG), that activates during visual perception of numerals, with widespread adjacent responses when numerals are used in calculation. Here, we reexamined the contribution of the IPS, SPL, and pITG to arithmetic by recording intracranial electroencephalography signals while participants solved addition problems. Behavioral results showed a classical problem size effect: RTs increased with the size of the operands. We then examined how high-frequency broadband (HFB) activity is modulated by problem size. As expected from previous fMRI findings, we showed that the total HFB activity in IPS and SPL sites increased with problem size. More surprisingly, pITG sites showed an initial burst of HFB activity that decreased as the operands got larger, yet with a constant integral over the whole trial, thus making these signals invisible to slow fMRI. Although parietal sites appear to have a more sustained function in arithmetic computations, the pITG may have a role of early identification of the problem difficulty, beyond merely digit recognition. Our results ask for a reevaluation of the current models of numerical cognition and reveal that the ventral temporal cortex contains regions specifically engaged in mathematical processing.

Crossmodal association of auditory and visual material properties in infants

The human perceptual system enables us to extract visual properties of an object’s material from auditory information. In monkeys, the neural basis underlying such multisensory association develops through experience of exposure to a material; material information could be processed in the posterior inferior temporal cortex, progressively from the high-order visual areas. In humans, however, the development of this neural representation remains poorly understood. Here, we demonstrated for the first time the presence of a mapping of the auditory material property with visual material (“Metal” and “Wood”) in the right temporal region in preverbal 4- to 8-month-old infants, using near-infrared spectroscopy (NIRS). Furthermore, we found that infants acquired the audio-visual mapping for a property of the “Metal” material later than for the “Wood” material, since infants form the visual property of “Metal” material after approximately 6 months of age. These findings indicate that multisensory processing of material information induces the activation of brain areas related to sound symbolism. Our findings also indicate that the material’s familiarity might facilitate the development of multisensory processing during the first year of life.

Posterior Inferotemporal Cortex Cells Use Multiple Input Pathways for Shape Encoding.

In the macaque monkey brain, posterior inferior temporal (PIT) cortex cells contribute to visual object recognition. They receive concurrent inputs from visual areas V4, V3, and V2. We asked how these different anatomical pathways shape PIT response properties by deactivating them while monitoring PIT activity in two male macaques. We found that cooling of V4 or V2|3 did not lead to consistent changes in population excitatory drive; however, population pattern analyses showed that V4-based pathways were more important than V2|3-based pathways. We did not find any image features that predicted decoding accuracy differences between both interventions. Using the HMAX hierarchical model of visual recognition, we found that different groups of simulated "PIT" units with different input histories (lacking "V2|3" or "V4" input) allowed for comparable levels of object-decoding performance and that removing a large fraction of "PIT" activity resulted in similar drops in performance as in the cooling experiments. We conclude that distinct input pathways to PIT relay similar types of shape information, with V1-dependent V4 cells providing more quantitatively useful information for overall encoding than cells in V2 projecting directly to PIT.SIGNIFICANCE STATEMENT Convolutional neural networks are the best models of the visual system, but most emphasize input transformations across a serial hierarchy akin to the primary "ventral stream" (V1 → V2 → V4 → IT). However, the ventral stream also comprises parallel "bypass" pathways: V1 also connects to V4, and V2 to IT. To explore the advantages of mixing long and short pathways in the macaque brain, we used cortical cooling to silence inputs to posterior IT and compared the findings with an HMAX model with parallel pathways.

Motivated attention and family risk for depression: Neuronal generator patterns at scalp elicited by lateralized aversive pictures reveal blunted emotional responsivity.

Behavioral and electrophysiologic evidence suggests that major depression (MDD) involves right parietotemporal dysfunction, a region activated by arousing affective stimuli. Building on prior event-related potential (ERP) findings (Kayser et al. 2016 NeuroImage 142:337–350), this study examined whether these abnormalities also characterize individuals at clinical high risk for MDD. We systematically explored the impact of family risk status and personal history of depression and anxiety on three distinct stages of emotional processing comprising the late positive potential (LPP). ERPs (72 channels) were recorded from 74 high and 53 low risk individuals (age 13–59 years, 58 male) during a visual half-field paradigm using highly-controlled pictures of cosmetic surgery patients showing disordered (negative) or healed (neutral) facial areas before or after treatment. Reference-free current source density (CSD) transformations of ERP waveforms were quantified by temporal principal components analysis (tPCA). Component scores of prominent CSD-tPCA factors sensitive to emotional content were analyzed via permutation tests and repeated measures ANOVA for mixed factorial designs with unstructured covariance matrix, including gender, age and clinical covariates. Factor-based distributed inverse solutions provided descriptive estimates of emotional brain activations at group level corresponding to hierarchical activations along ventral visual processing stream. Risk status affected emotional responsivity (increased positivity to negative-than-neutral stimuli) overlapping early N2 sink (peak latency 212 ms), P3 source (385 ms), and a late centroparietal source (630 ms). High risk individuals had reduced right-greater-than-left emotional lateralization involving occipitotemporal cortex (N2 sink) and bilaterally reduced emotional effects involving posterior cingulate (P3 source) and inferior temporal cortex (630 ms) when compared to those at low risk. While the early emotional effects were enhanced for left hemifield (right hemisphere) presentations, hemifield modulations did not differ between risk groups, suggesting top-down rather than bottom-up effects of risk. Groups did not differ in their stimulus valence or arousal ratings. Similar effects were seen for individuals with a lifetime history of depression or anxiety disorder in comparison to those without. However, there was no evidence that risk status and history of MDD or anxiety disorder interacted in their impact on emotional responsivity, suggesting largely independent attenuation of attentional resource allocation to enhance perceptual processing of motivationally salient stimuli. These findings further suggest that a deficit in motivated attention preceding conscious awareness may be a marker of risk for depression.

Representational Similarity Mapping of Distributional Semantics in Left Inferior Frontal, Middle Temporal, and Motor Cortex.

Language comprehension engages a distributed network of frontotemporal, parietal, and sensorimotor regions, but it is still unclear how meaning of words and their semantic relationships are represented and processed within these regions and to which degrees lexico-semantic representations differ between regions and semantic types. We used fMRI and representational similarity analysis to relate word-elicited multivoxel patterns to semantic similarity between action and object words. In left inferior frontal (BA 44-45-47), left posterior middle temporal and left precentral cortex, the similarity of brain response patterns reflected semantic similarity among action-related verbs, as well as across lexical classes-between action verbs and tool-related nouns and, to a degree, between action verbs and food nouns, but not between action verbs and animal nouns. Instead, posterior inferior temporal cortex exhibited a reverse response pattern, which reflected the semantic similarity among object-related nouns, but not action-related words. These results show that semantic similarity is encoded by a range of cortical areas, including multimodal association (e.g., anterior inferior frontal, posterior middle temporal) and modality-preferential (premotor) cortex and that the representational geometries in these regions are partly dependent on semantic type, with semantic similarity among action-related words crossing lexical-semantic category boundaries.

Representation of Perceptual Color Space in Macaque Posterior Inferior Temporal Cortex (the V4 Complex).

The lateral geniculate nucleus is thought to represent color using two populations of cone-opponent neurons [L vs M; S vs (L + M)], which establish the cardinal directions in color space (reddish vs cyan; lavender vs lime). How is this representation transformed to bring about color perception? Prior work implicates populations of glob cells in posterior inferior temporal cortex (PIT; the V4 complex), but the correspondence between the neural representation of color in PIT/V4 complex and the organization of perceptual color space is unclear. We compared color-tuning data for populations of glob cells and interglob cells to predictions obtained using models that varied in the color-tuning narrowness of the cells, and the color preference distribution across the populations. Glob cells were best accounted for by simulated neurons that have nonlinear (narrow) tuning and, as a population, represent a color space designed to be perceptually uniform (CIELUV). Multidimensional scaling and representational similarity analyses showed that the color space representations in both glob and interglob populations were correlated with the organization of CIELUV space, but glob cells showed a stronger correlation. Hue could be classified invariant to luminance with high accuracy given glob responses and above-chance accuracy given interglob responses. Luminance could be read out invariant to changes in hue in both populations, but interglob cells tended to prefer stimuli having luminance contrast, regardless of hue, whereas glob cells typically retained hue tuning as luminance contrast was modulated. The combined luminance/hue sensitivity of glob cells is predicted for neurons that can distinguish two colors of the same hue at different luminance levels (orange/brown).

Crossmodal Association of Visual and Haptic Material Properties of Objects in the Monkey Ventral Visual Cortex

Just by looking at an object, we can recognize its non-visual properties, such as hardness. The visual recognition of non-visual object properties is generally accurate [1], and influences actions toward the object [2]. Recent studies suggest that, in the primate brain, this may involve the ventral visual cortex, which represents objects in a way that reflects not only visual but also non-visual object properties, such as haptic roughness, hardness, and weight [3-7]. This new insight raises a fundamental question: how does the visual cortex come to represent non-visual properties--knowledge that cannot be acquired directly through vision? Here we addressed this unresolved question using fMRI in macaque monkeys. Specifically, we explored whether and how simple visuo-haptic experience--just seeing and touching objects made of various materials--can shape representational content in the visual cortex. We measured brain activity evoked by viewing images of objects before and after the monkeys acquired the visuo-haptic experience and decoded the representational space from the activity patterns [8]. We show that simple long-term visuo-haptic experience greatly impacts representation in the posterior inferior temporal cortex, the higher ventral visual cortex. After the experience, but not before, the activity pattern in this region well reflected the haptic material properties of the experienced objects. Our results suggest that neural representation of non-visual object properties in the visual cortex emerges through long-term crossmodal exposure to objects. This highlights the importance of unsupervised learning of crossmodal associations through everyday experience [9-12] for shaping representation in the visual cortex.