István Ákos Mórocz

Using fMRI to distinguish components of the multiple object tracking task.

Multiple object tracking (MOT) has proven to be a powerful technique for studying sustained selective attention. However, surprisingly little is known about its underlying neural mechanisms. Previous fMRI investigations have identified several brain areas thought to be involved in MOT, but there were disagreements between the studies, none distinguished between the act of tracking targets and the act of attending targets, and none attempted to determine which of these brain areas interact with each other. Here we address these three issues. First, using more observers and a random effects analysis, we show that some of the previously identified areas may not play a specific role in MOT. Second, we show that the frontal eye fields (FEF), the anterior intraparietal sulcus (AIPS), the superior parietal lobule (SPL), the posterior intraparietal sulcus (PIPS) and the human motion area (MT+) are differentially activated by the act of tracking, as distinguished from the act of attention. Finally, by using an algorithm modified from the computer science literature, we were able to map the interactions between these brain areas.

Volumetric Quantification of Brain Swelling after Hypobaric Hypoxia Exposure

We applied a novel MR imaging technique to investigate the effect of acute mountain sickness on cerebral tissue water. Nine volunteers were exposed to hypobaric hypoxia corresponding to 4572 m altitude for 32 h. Such an exposure may cause acute mountain sickness. We imaged the brains of the volunteers before and at 32 h of hypobaric exposure with two different MRI techniques with subsequent data processing. (1) Brain volumes were calculated from 3D MRI data sets by applying a computerized brain segmentation algorithm. For this specific purpose a novel adaptive 3D segmentation program was used with an automatic correction algorithm for RF field inhomogeneity. (2) T(2) decay rates were analyzed in the white matter. The results demonstrated that a significant brain swelling of 36.2 +/- 19.6 ml (2.77 +/- 1.47%, n = 9, P < 0.001) developed after the 32-h hypobaric hypoxia exposure with a maximal observed volume increase of 5.8% (71.3 ml). These volume changes were significant only for the gray matter structures in contrast to the unremarkable changes seen in the white matter. The same study repeated 3 weeks later in 6 of 9 original subjects demonstrated that the brains recovered and returned approximately to the initially determined sea-level brain volume while hypobaric hypoxia exposure once again led to a significant new brain swelling (24.1 +/- 12.1 ml, 1.92 +/- 0.96%, n = 6, P < 0.005). On the contrary, the T(2) mapping technique did not reveal any significant effect of hypobaria on white matter. We present here a technique which is able to detect reversible brain volume changes as they may occur in patients with diffuse brain edema or increased cerebral blood volume, and which may represent a useful noninvasive tool for future evaluations of antiedematous drugs.

Auditory processing abnormalities in schizotypal personality disorder: an fMRI experiment using tones of deviant pitch and duration.

BACKGROUND One of the cardinal features of schizotypal personality disorder (SPD) is language abnormalities. The focus of this study was to determine whether or not there are also processing abnormalities of pure tones differing in pitch and duration in SPD. METHODS Thirteen neuroleptic-naïve male subjects met full criteria for SPD and were group-matched on age and parental socio-economic status to 13 comparison subjects. Verbal learning was measured with the California Verbal Learning Test. Heschls gyrus volumes were measured using structural MRI. Whole-brain fMRI activation patterns in an auditory task of listening to tones including pitch and duration deviants were compared between SPD and control subjects. In a second and separate ROI analysis we found that peak activation in superior temporal gyrus (STG), Brodmann Areas 41 and 42, was correlated with verbal learning and clinical measures derived from the SCID-II interview. RESULTS In the region of the STG, SPD subjects demonstrated more activation to pitch deviants bilaterally (p<0.001); and to duration deviants in the left hemisphere (p=0.005) (two-sample t). SPD subjects also showed more bilateral parietal cortex activation to duration deviants. In no region did comparison subjects activate more than SPD subjects in either experiment. Exploratory correlations for SPD subjects suggest a relationship between peak activation on the right for deviant tones in the pitch experiment with odd speech and impaired verbal learning. There was no difference between groups on Heschls gyrus volume. CONCLUSIONS These data suggest that SPD subjects have inefficient or hyper-responsive processing of pure tones both in terms of pitch and duration deviance that is not attributable to smaller Heschls gyrus volumes. Finally, these auditory processing abnormalities may have significance for the odd speech heard in some SPD subjects and downstream language and verbal learning deficits.

The benefit of symbols: monkeys show linear, human-like, accuracy when using symbols to represent scalar value

When humans and animals estimate numbers of items, their error rate is proportional to the number. To date, however, only humans show the capacity to represent large numbers symbolically, which endows them with increased precision, especially for large numbers, and with tools for manipulating numbers. This ability depends critically on our capacity to acquire and represent explicit symbols. Here we show that when rhesus monkeys are trained to use an explicit symbol system, they too show more precise, and linear, scaling than they do using a one-to-one corresponding numerosity representation. We also found that when taught two different types of representations for reward amount, the monkeys systematically undervalued the less precise representation. The results indicate that monkeys, like humans, can learn alternative mechanisms for representing a single value scale and that performance variability and relative value depend on the distinguishability of each representation.

Spatio-temporal models of mental processes from fMRI

Understanding the highly complex, spatially distributed and temporally organized phenomena entailed by mental processes using functional MRI is an important research problem in cognitive and clinical neuroscience. Conventional analysis methods focus on the spatial dimension of the data discarding the information about brain function contained in the temporal dimension. This paper presents a fully spatio-temporal multivariate analysis method using a state-space model (SSM) for brain function that yields not only spatial maps of activity but also its temporal structure along with spatially varying estimates of the hemodynamic response. Efficient algorithms for estimating the parameters along with quantitative validations are given. A novel low-dimensional feature-space for representing the data, based on a formal definition of functional similarity, is derived. Quantitative validation of the model and the estimation algorithms is provided with a simulation study. Using a real fMRI study for mental arithmetic, the ability of this neurophysiologically inspired model to represent the spatio-temporal information corresponding to mental processes is demonstrated. Moreover, by comparing the models across multiple subjects, natural patterns in mental processes organized according to different mental abilities are revealed.

Symbol addition by monkeys provides evidence for normalized quantity coding

Significance Symbol-literate monkeys can be trained to combine, or add, pairs of large numbers. They transfer to a novel symbol set, ruling out memorization of each symbol pair. Their addition behavior indicates an underlying relative scaling of magnitude. Weber’s law can be explained either by a compressive scaling of sensory response with stimulus magnitude or by a proportional scaling of response variability. These two mechanisms can be distinguished by asking how quantities are added or subtracted. We trained Rhesus monkeys to associate 26 distinct symbols with 0–25 drops of reward, and then tested how they combine, or add, symbolically represented reward magnitude. We found that they could combine symbolically represented magnitudes, and they transferred this ability to a novel symbol set, indicating that they were performing a calculation, not just memorizing the value of each combination. The way they combined pairs of symbols indicated neither a linear nor a compressed scale, but rather a dynamically shifting, relative scaling.

Subitizing is sensitive to the arrangement of objects.

Subitizing is a fast and accurate enumeration process of small sets of usually less than four objects. Several models were proposed in the literature. Critically, only pattern recognition theory suggests that subitizing performance is sensitive to the arrangement of the array. In our study, arrays of dots in random or canonical arrangements were enumerated. The subitizing range was larger and the reaction time slope was less steep in the canonical arrangements. When noise was added to the canonical pattern, the reaction time slope was proportional to the amount of noise. Moreover, arrangement has a stronger effect on sets with more than four objects. These results support the pattern recognition model of subitizing.

Rapid full-brain fMRI with an accelerated multi shot 3D EPI sequence using both UNFOLD and GRAPPA

The desire to understand complex mental processes using functional MRI drives development of imaging techniques that scan the whole human brain at a high spatial and temporal resolution. In this work, an accelerated multishot three‐dimensional echo‐planar imaging sequence is proposed to increase the temporal resolution of these studies. A combination of two modern acceleration techniques, UNFOLD and GRAPPA is used in the secondary phase encoding direction to reduce the scan time effectively. The sequence (repetition time of 1.02 s) was compared with standard two‐dimensional echo‐planar imaging (3 s) and multishot three‐dimensional echo‐planar imaging (3 s) sequences with both block design and event‐related functional MRI paradigms. With the same experimental setup and imaging time, the temporal resolution improvement with our sequence yields similar activation regions in the block design functional MRI paradigm with slightly increased t‐scores. Moreover, additional information on the timing of rapid dynamic changes was extracted from accelerated images for the case of the event related complex mental paradigm. Magn Reson Med, 2012.

State-space models of mental processes from fMRI

In addition to functional localization and integration, the problem of determining whether the data encode some information about the mental state of the subject, and if so, how this information is represented has become an important research agenda in functional neuroimaging. Multivariate classifiers, commonly used for brain state decoding, are restricted to simple experimental paradigms with a fixed number of alternatives and are limited in their representation of the temporal dimension of the task. Moreover, they learn a mapping from the data to experimental conditions and therefore do not explain the intrinsic patterns in the data. In this paper, we present a data-driven approach to building a spatio-temporal representation of mental processes using a state-space formalism, without reference to experimental conditions. Efficient Monte Carlo algorithms for estimating the parameters of the model along with a method for model-size selection are developed. The advantages of such a model in determining the mental-state of the subject over pattern classifiers are demonstrated using an fMRI study of mental arithmetic.

Unsupervised learning of brain states from fMRI data

The use of multivariate pattern recognition for the analysis of neural representations encoded in fMRI data has become a significant research topic, with wide applications in neuroscience and psychology. A popular approach is to learn a mapping from the data to the observed behavior. However, identifying the instantaneous cognitive state without reference to external conditions is a relatively unexplored problem and could provide important insights into mental processes. In this paper, we present preliminary but promising results from the application of an unsupervised learning technique to identify distinct brain states. The temporal ordering of the states were seen to be synchronized with the experimental conditions, while the spatial distribution of activity in a state conformed with the expected functional recruitment.