Stimulus repetition probability does not affect repetition suppression in macaque inferior temporal cortex.

Recent human functional magnetic resonance imaging studies (Summerfield C, Trittschuh EH, Monti JM, Mesulam MM, Egner T. 2008. Neural repetition suppression reflects fulfilled perceptual expectations. Nat Neurosci. 11:1004-1006.) showed that adaptation or repetition suppression is affected by contextual factors related to perceptual expectations, suggesting that adaptation results from a fulfillment of perceptual expectation or a reduction in prediction error. This view contrasts with the bottom-up fatigue or sharpening mechanisms of adaptation proposed in single-cell studies. We examined whether stimulus repetition probability affects adaptation of spiking activity and local field potentials (LFPs) in macaque inferior temporal (IT) cortex, using a protocol similar to that of Summerfield et al. Monkeys were exposed to 2 randomly interleaved trials, each consisting of either 2 identical (rep trial) or 2 different stimuli (alt trial). Trials were presented in repetition (rep) blocks consisting of 75% of rep trials and 25% of alt trials or in alternation (alt) blocks having opposite repetition probabilities. For both spiking and LFP activities, the stimulus-selective adaptation did not differ significantly between rep and alt blocks. The number of preceding rep or alt trials and the trial position within a block did not affect adaptation. This absence of any effect of stimulus repetition probability on adaptation suggests that adaptation in IT is not caused by contextual factors related to perceptual expectation.

[1]  J. Ringo,et al.  Investigation of long term recognition and association memory in unit responses from inferotemporal cortex , 1993, Experimental Brain Research.

[2]  Jim M. Monti,et al.  Neural repetition suppression reflects fulfilled perceptual expectations , 2008, Nature Neuroscience.

[3]  K. Grill-Spector,et al.  Repetition and the brain: neural models of stimulus-specific effects , 2006, Trends in Cognitive Sciences.

[4]  J. Maunsell,et al.  Feature-based attention in visual cortex , 2006, Trends in Neurosciences.

[5]  Antonio Torralba,et al.  LabelMe: A Database and Web-Based Tool for Image Annotation , 2008, International Journal of Computer Vision.

[6]  Yasushi Miyashita,et al.  Generation of fractal patterns for probing the visual memory , 1991, Neuroscience Research.

[7]  R. Freeman,et al.  Neurometabolic coupling in cerebral cortex reflects synaptic more than spiking activity , 2007, Nature Neuroscience.

[8]  R. Desimone,et al.  The Effects of Visual Stimulation and Selective Visual Attention on Rhythmic Neuronal Synchronization in Macaque Area V4 , 2008, The Journal of Neuroscience.

[9]  Joris Vangeneugden,et al.  Stimulus Similarity-Contingent Neural Adaptation Can Be Time and Cortical Area Dependent , 2008, The Journal of Neuroscience.

[10]  R. Desimone,et al.  A neural mechanism for working and recognition memory in inferior temporal cortex. , 1991, Science.

[11]  E. Rolls,et al.  Responses of neurons in the inferior temporal cortex in short term and serial recognition memory tasks , 2004, Experimental Brain Research.

[12]  Aaron R. Seitz,et al.  Dissociable Neural Effects of Long-term Stimulus–Reward Pairing in Macaque Visual Cortex , 2010, Journal of Cognitive Neuroscience.

[13]  G L Gerstein,et al.  Single-unit activity in temporal association cortex of the monkey. , 1967, Journal of neurophysiology.

[14]  R. Desimone,et al.  Neural mechanisms for visual memory and their role in attention. , 1996, Proceedings of the National Academy of Sciences of the United States of America.

[15]  Karl J. Friston,et al.  A theory of cortical responses , 2005, Philosophical Transactions of the Royal Society B: Biological Sciences.

[16]  E. Miller,et al.  Habituation-like decrease in the responses of neurons in inferior temporal cortex of the macaque , 1991, Visual Neuroscience.

[17]  Shimon Marom,et al.  Selective Adaptation in Networks of Cortical Neurons , 2003, The Journal of Neuroscience.

[18]  G. Orban,et al.  How task-related are the responses of inferior temporal neurons? , 1995, Visual Neuroscience.

[19]  J. Ringo.  Stimulus specific adaptation in inferior temporal and medial temporal cortex of the monkey , 1996, Behavioural Brain Research.

[20]  I. Riches,et al.  The effects of visual stimulation and memory on neurons of the hippocampal formation and the neighboring parahippocampal gyrus and inferior temporal cortex of the primate , 1991, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[21]  G. Orban,et al.  Selectivity of Neuronal Adaptation Does Not Match Response Selectivity: A Single-Cell Study of the fMRI Adaptation Paradigm , 2006, Neuron.

[22]  R. Desimone,et al.  Selective attention gates visual processing in the extrastriate cortex. , 1985, Science.

[23]  D. B. Bender,et al.  Visual Receptive Fields of Neurons in Inferotemporal Cortex of the Monkey , 1969, Science.

[24]  Nikos K. Logothetis,et al.  The effect of a serotonin-induced dissociation between spiking and perisynaptic activity on BOLD functional MRI , 2008, Proceedings of the National Academy of Sciences.

[25]  Britt Anderson,et al.  Effects of temporal context and temporal expectancy on neural activity in inferior temporal cortex , 2008, Neuropsychologia.

[26]  C. Olson,et al.  Repetition suppression in monkey inferotemporal cortex: relation to behavioral priming. , 2007, Journal of neurophysiology.

[27]  M. W. Brown,et al.  Differential neuronal encoding of novelty, familiarity and recency in regions of the anterior temporal lobe , 1998, Neuropharmacology.

[28]  John Duncan,et al.  A neural basis for visual search in inferior temporal cortex , 1993, Nature.

[29]  Christopher J. Aura,et al.  Divergence of fMRI and neural signals in V1 during perceptual suppression in the awake monkey , 2008, Nature Neuroscience.

[30]  W. Regehr,et al.  Short-term synaptic plasticity. , 2002, Annual review of physiology.

[31]  C. Summerfield,et al.  Expectation (and attention) in visual cognition , 2009, Trends in Cognitive Sciences.

[32]  M. Mishkin,et al.  Learning increases stimulus salience in anterior inferior temporal cortex of the macaque. , 2001, Journal of neurophysiology.

[33]  Elie Bienenstock,et al.  Precise Spatiotemporal Patterns among Visual Cortical Areas and Their Relation to Visual Stimulus Processing , 2010, The Journal of Neuroscience.

[34]  J. Pernier,et al.  Oscillatory γ-Band (30–70 Hz) Activity Induced by a Visual Search Task in Humans , 1997, The Journal of Neuroscience.

[35]  N. Logothetis,et al.  Neurophysiological investigation of the basis of the fMRI signal , 2001, Nature.

[36]  Yevgeniy B. Sirotin,et al.  Anticipatory haemodynamic signals in sensory cortex not predicted by local neuronal activity. , 2009, Nature.

[37]  Xoana G. Troncoso,et al.  Microsaccades: a neurophysiological analysis , 2009, Trends in Neurosciences.

[38]  Yan Liu,et al.  Time course and stimulus dependence of repetition-induced response suppression in inferotemporal cortex. , 2009, Journal of neurophysiology.

[39]  D. Heeger,et al.  The Normalization Model of Attention , 2009, Neuron.

[40]  Caspar M. Schwiedrzik,et al.  Stimulus Predictability Reduces Responses in Primary Visual Cortex , 2010, The Journal of Neuroscience.

[41]  W. Newsome,et al.  Local Field Potential in Cortical Area MT: Stimulus Tuning and Behavioral Correlations , 2006, The Journal of Neuroscience.

[42]  R. Vogels,et al.  Effects of adaptation on the stimulus selectivity of macaque inferior temporal spiking activity and local field potentials. , 2010, Cerebral cortex.

[43]  E. Niebur,et al.  Neural Correlates of High-Gamma Oscillations (60–200 Hz) in Macaque Local Field Potentials and Their Potential Implications in Electrocorticography , 2008, The Journal of Neuroscience.

[44]  Ralf Engbert,et al.  Microsaccades uncover the orientation of covert attention , 2003, Vision Research.

[45]  J. Pernier,et al.  Oscillatory gamma-band (30-70 Hz) activity induced by a visual search task in humans. , 1997, The Journal of neuroscience : the official journal of the Society for Neuroscience.