Saturday, December 29, 2007

Inferring spike trains from local field potentials

Rasch MJ, Gretton A, Murayama Y, Maass W, Logothetis NK
J Neurophysiol. 2007 Dec 26

We investigated whether it is possible to infer spike trains solely on the basis of the underling local field potentials (LFPs). Employing support vector machines and linear regression models, we found that in the primary visual cortex (V1) of monkeys, spikes can indeed be inferred from LFPs, at least with moderate success. Although there is a considerable degree of variation across electrodes, the low-frequency structure in spike trains (in the 100 ms range) can be inferred with reasonable accuracy, whereas exact spike positions are not reliably predicted. Two kinds of features of the LFP are exploited for prediction: the frequency power of bands in the high gamma-range (40-90 Hz), and information contained in low-frequency oscillations (<10 Hz), where both phase and power modulations are informative. Information analysis revealed that both features code (mainly) independent aspects of the spike-to-LFP relationship, with the low-frequency LFP phase coding for temporally clustered spiking activity. Although both features and prediction quality are similar during semi-natural movie stimuli and spontaneous activity, prediction performance during spontaneous activity degrades much more slowly with increasing electrode distance. The general trend of data obtained with anesthetized animals is qualitatively mirrored in that of a more limited data set recorded in V1 of awake monkeys. In contrast to the cortical field potentials, thalamic LFPs (e.g. LFPs derived from recordings in dLGN) hold no useful information for predicting spiking activity.

PMID: 18160425

Wednesday, December 26, 2007

Single neuron studies of inferior temporal cortex

Gross CG.
Neuropsychologia. 2007 Nov 21

This paper reviews our experiments on the response properties of single neurons in inferior temporal (IT) cortex in the monkey that were carried out starting in 1965. It describes situational factors that led us to find neurons sensitive to images of faces and hands and summarizes the basic sensory properties of IT neurons. Subsequent developments on the cognitive properties of IT neurons and on imaging the responses of human temporal cortex to facial images are outlined. Finally, this paper summarizes recent results on fMRI imaging of the responses of temporal cortex to facial images.

PMID: 18155735

Fulltext: Science Direct

Tuesday, December 18, 2007

Individual faces elicit distinct response patterns in human anterior temporal cortex

Kriegeskorte N, Formisano E, Sorger B, Goebel R.
Proc Natl Acad Sci U S A. 2007 Dec 11

Visual face identification requires distinguishing between thousands of faces we know. This computational feat involves a network of brain regions including the fusiform face area (FFA) and anterior inferotemporal cortex (aIT), whose roles in the process are not well understood. Here, we provide the first demonstration that it is possible to discriminate cortical response patterns elicited by individual face images with high-resolution functional magnetic resonance imaging (fMRI). Response patterns elicited by the face images were distinct in aIT but not in the FFA. Individual-level face information is likely to be present in both regions, but our data suggest that it is more pronounced in aIT. One interpretation is that the FFA detects faces and engages aIT for identification.

PMID: 18077383

Retinotopy of the face aftereffect.

Afraz SR, Cavanagh P.
Vision Res. 2007 Dec 11

Physiological results for the size of face-specific units in inferotemporal cortex (IT) support an extraordinarily large range of possible sizes-from 2.5 degrees to 30 degrees or more. We use a behavioral test of face-specific aftereffects to measure the face analysis regions and find a coarse retinotopy consistent with receptive fields of intermediate size (10 degrees -12 degrees at 3 degrees eccentricity). In the first experiment, observers were adapted to a single face at 3 degrees from fixation. A test (a morph of the face and its anti-face) was then presented at different locations around fixation and subjects classified it as face or anti-face. The face aftereffect (FAE) was not constant at all test locations-it dropped to half its maximum value for tests 5 degrees from the adapting location. Simultaneous adaptation to both a face and its anti-face, placed at opposite locations across fixation, produced two separate regions of opposite aftereffects. However, with four stimuli, faces alternating with anti-faces equally spaced around fixation, the FAE was greatly reduced at all locations, implying a fairly coarse localization of the aftereffect. In the second experiment, observers adapted to a face and its anti-face presented either simultaneously or in alternation. Results showed that the simultaneous presentation of a face and its anti-face leads to stronger FAEs than sequential presentation, suggesting that face processing has a dynamic nature and its region of analysis is sharpened when there is more than one face in the scene. In the final experiment, a face and two anti-face flankers with different spatial offsets were presented during adaptation and the FAE was measured at the face location. Results showed that FAE at the face location was inhibited more as the distance of anti-face flankers to the face stimulus was reduced. This confirms the spatial extent of face analysis regions in a test with a fixed number of stimuli where only distance varied.

PMID: 18078975

Complementary circuits connecting the orbital and medial prefrontal networks with the temporal, insular, and opercular cortex in the macaque monkey

Saleem KS, Kondo H, Price JL
J Comp Neurol. 2008 Feb 1;506(4):659-93.

The origin and termination of axonal connections between the orbital and medial prefrontal cortex (OMPFC) and the temporal, insular, and opercular cortex have been analyzed with anterograde and retrograde axonal tracers, injected in the OMPFC or temporal cortex. The results show that there are two distinct, complementary, and reciprocal neural systems, related to the previously defined "orbital" and "medial" prefrontal networks. The orbital prefrontal network, which includes areas in the central and lateral part of the orbital cortex, is connected with vision-related areas in the inferior temporal cortex (especially area TEav) and the fundus and ventral bank of the superior temporal sulcus (STSf/v), and with somatic sensory-related areas in the frontal operculum (OPf) and dysgranular insular area (Id). No connections were found between the orbital network and auditory areas. The orbital network is also connected with taste and olfactory cortical areas and the perirhinal cortex and appears to be involved in assessment of sensory objects, especially food. The medial prefrontal network includes areas on the medial surface of the frontal lobe, medial orbital areas, and two caudolateral orbital areas. It is connected with the rostral superior temporal gyrus (STGr) and the dorsal bank of the superior temporal sulcus (STSd). This region is rostral to the auditory parabelt areas, and there are only relatively light connections between the auditory areas and the medial network. This system, which is also connected with the entorhinal, parahippocampal, and cingulate/retrosplenial cortex, may be involved in emotion and other self-referential processes. J. Comp. Neurol. 506:659-693, 2008. (c) 2007 Wiley-Liss, Inc.

PMID: 18067141

Thursday, December 6, 2007

Neural mechanisms of visual categorization: Insights from neurophysiology

Freedman DJ, Miller EK.
Neurosci Biobehav Rev. 2007 Aug 15

How does the brain recognize the meaning of sensory stimuli? Through experience, we easily learn to group stimuli into meaningful categories such as "chair", "table" and "vehicle". Although much is known about how the brain processes and encodes basic visual features (e.g. color, orientation, and motion direction), much less is known about how the brain learns and represents the behavioral relevance, or category, of stimuli. This article will review a number of recent experiments which suggest that neuronal activity in primate prefrontal, temporal and parietal cortical areas likely plays significant, though complementary, roles in visual categorization and category learning.

PMID: 17950874

Fulltext: sciencedirect

Surface-based and probabilistic atlases of primate cerebral cortex

Van Essen DC, Dierker DL.
Neuron. 2007 Oct 25;56(2):209-25

Brain atlases play an increasingly important role in neuroimaging, as they are invaluable for analysis, visualization, and comparison of results across studies. For both humans and macaque monkeys, digital brain atlases of many varieties are in widespread use, each having its own strengths and limitations. For studies of cerebral cortex there is particular utility in hybrid atlases that capitalize on the complementary nature of surface and volume representations, are based on a population average rather than an individual brain, and include measures of variation as well as averages. Linking different brain atlases to one another and to online databases containing a growing body of neuroimaging data will enable powerful forms of data mining that accelerate discovery and improve research efficiency.

PMID: 17964241


Trade-off between object selectivity and tolerance in monkey inferotemporal cortex

Zoccolan D, Kouh M, Poggio T, DiCarlo JJ
J Neurosci. 2007 Nov 7;27(45):12292-307

Object recognition requires both selectivity among different objects and tolerance to vastly different retinal images of the same object, resulting from natural variation in (e.g.) position, size, illumination, and clutter. Thus, discovering neuronal responses that have object selectivity and tolerance to identity-preserving transformations is fundamental to understanding object recognition. Although selectivity and tolerance are found at the highest level of the primate ventral visual stream [the inferotemporal cortex (IT)], both properties are highly varied and poorly understood. If an IT neuron has very sharp selectivity for a unique combination of object features ("diagnostic features"), this might automatically endow it with high tolerance. However, this relationship cannot be taken as given; although some IT neurons are highly object selective and some are highly tolerant, the empirical connection of these key properties is unknown. In this study, we systematically measured both object selectivity and tolerance to different identity-preserving image transformations in the spiking responses of a population of monkey IT neurons. We found that IT neurons with high object selectivity typically have low tolerance (and vice versa), regardless of how object selectivity was quantified and the type of tolerance examined. The discovery of this trade-off illuminates object selectivity and tolerance in IT and unifies a range of previous, seemingly disparate results. This finding also argues against the idea that diagnostic conjunctions of features guarantee tolerance. Instead, it is naturally explained by object recognition models in which object selectivity is built through AND-like tuning mechanisms.

PMID: 17989294


The representation of multiple objects in prefrontal neuronal delay activity

Warden MR, Miller EK
Cereb Cortex. 2007 Sep;17 Suppl 1:i41-50.

The ability to retain multiple items in short-term memory is fundamental for intelligent behavior, yet little is known about its neural basis. To explore the mechanisms underlying this ability, we trained 2 monkeys to remember a sequence of 2 objects across a short delay. We then recorded the activity of neurons from the lateral prefrontal cortex during task performance and found that most neurons had activity that depended on the identity of both objects while a minority reflected just one object. Further, the activity driven by a particular combination of objects was not a simple addition of the activity elicited by individual objects. Instead, the representation of the first object was altered by the addition of the second object to memory, and the form of this change was not systematically predictable. These results indicate that multiple objects are not stored in separate groups of prefrontal neurons. Rather, they are represented by a single population of neurons in a complex fashion. We also found that the strength of the memory trace associated with each object decayed over time, leading to a relatively stronger representation of more recently seen objects. This is a potential mechanism for representing the temporal order of objects.

PMID: 17726003


Electrical Stimulation of the Midbrain for Hearing Restoration: Insight into the Functional Organization of the Human Central Auditory System

Hubert H. Lim, Thomas Lenarz, Gert Joseph, Rolf-Dieter Battmer, Amir Samii, Madjid Samii, James F. Patrick, and Minoo Lenarz

The cochlear implant can restore speech perception in patients with sensorineural hearing loss. However, it is ineffective for those without an implantable cochlea or a functional auditory nerve. These patients can be implanted with the auditory brainstem implant (ABI), which stimulates the surface of the cochlear nucleus. Unfortunately, the ABI has achieved limited success in its main patient group [i.e., those with neurofibromatosis type 2 (NF2)] and requires a difficult surgical procedure. These limitations have motivated us to develop a new hearing prosthesis that stimulates the midbrain with a penetrating electrode array. We recently implanted three patients with the auditory midbrain implant (AMI), and it has proven to be safe with minimal movement over time. The AMI provides loudness, pitch, temporal, and directional cues, features that have shown to be important for speech perception and more complex sound processing. Thus far, all three patients obtain enhancements in lip reading capabilities and environmental awareness and some improvements in speech perception comparable with that of NF2 ABI patients. Considering that our midbrain target is more surgically exposable than the cochlear nucleus, this argues for the use of the AMI as an alternative to the ABI. Fortunately, we were able to stimulate different midbrain regions in our patients and investigate the functional organization of the human central auditory system. These findings provide some insight into how we may need to stimulate the midbrain to improve hearing performance with the AMI.