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Journal articles on the topic 'Association cortex'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Taira, Masato, and Narumi Katsuyama. "Visual association cortex." Journal of Japan Society for Fuzzy Theory and Intelligent Informatics 18, no. 3 (2006): 377–82. http://dx.doi.org/10.3156/jsoft.18.3_377.

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2

Culham, Jody. "Dissociations within Association Cortex." Neuron 33, no. 3 (2002): 318–20. http://dx.doi.org/10.1016/s0896-6273(02)00584-6.

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3

Zeki, Semir. "The visual association cortex." Current Opinion in Neurobiology 3, no. 2 (1993): 155–59. http://dx.doi.org/10.1016/0959-4388(93)90203-b.

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4

Kaas, Jon H. "The transformation of association cortex into sensory cortex." Brain Research Bulletin 50, no. 5-6 (1999): 425. http://dx.doi.org/10.1016/s0361-9230(99)00176-8.

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5

Gisiger, T. "Computational models of association cortex." Current Opinion in Neurobiology 10, no. 2 (2000): 250–59. http://dx.doi.org/10.1016/s0959-4388(00)00075-1.

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6

GREEN, RONALD. "Heteromodal Association Cortex in Schizophrenia." American Journal of Psychiatry 161, no. 9 (2004): 1723—a—1724. http://dx.doi.org/10.1176/appi.ajp.161.9.1723-a.

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7

Pearlson, Godfrey D., Patrick E. Barta, Thomas E. Schlaepfer, Richard G. Petty, Allen Y. Tien, and Iain K. McGilchrist. "Heteromodal association cortex in schizophrenia." Schizophrenia Research 15, no. 1-2 (1995): 95. http://dx.doi.org/10.1016/0920-9964(95)95295-k.

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8

Naya, Yuji. "Declarative association in the perirhinal cortex." Neuroscience Research 113 (December 2016): 12–18. http://dx.doi.org/10.1016/j.neures.2016.07.001.

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9

Schlaepfer, T. E., and G. Pearlson. "Heteromodal association cortex involvement in schizophrenia." European Psychiatry 17 (May 2002): 87. http://dx.doi.org/10.1016/s0924-9338(02)80399-6.

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10

Van Hoesen, Gary W. "The modern concept of association cortex." Current Opinion in Neurobiology 3, no. 2 (1993): 150–54. http://dx.doi.org/10.1016/0959-4388(93)90202-a.

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11

Bueti, Domenica, Bahador Bahrami, and Vincent Walsh. "Sensory and Association Cortex in Time Perception." Journal of Cognitive Neuroscience 20, no. 6 (2008): 1054–62. http://dx.doi.org/10.1162/jocn.2008.20060.

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The recent upsurge of interest in brain mechanisms of time perception is beginning to converge on some new starting points for investigating this long under studied aspect of our experience. In four experiments, we asked whether disruption of normal activity in human MT/V5 would interfere with temporal discrimination. Although clearly associated with both spatial and motion processing, MT/V5 has not yet been implicated in temporal processes. Following predictions from brain imaging studies that have shown the parietal cortex to be important in human time perception, we also asked whether disruption of either the left or right parietal cortex would interfere with time perception preferentially in the auditory or visual domain. The results show that the right posterior parietal cortex is important for timing of auditory and visual stimuli and that MT/V5 is necessary for timing only of visual events.

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12

Anders, Silke, Niels Birbaumer, Bettina Sadowski, et al. "Parietal somatosensory association cortex mediates affective blindsight." Nature Neuroscience 7, no. 4 (2004): 339–40. http://dx.doi.org/10.1038/nn1213.

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13

PEARLSON, G., R. PETTY, C. ROSS, and A. TIEN. "Schizophrenia: A disease of heteromodal association cortex?" Neuropsychopharmacology 14, no. 1 (1996): 1–17. http://dx.doi.org/10.1016/s0893-133x(96)80054-6.

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14

Harrison, Jean B., Linda W. Dickerson, Suying Song, and Jennifer S. Buchwald. "Cat-P300 present after association cortex ablation." Brain Research Bulletin 24, no. 4 (1990): 551–60. http://dx.doi.org/10.1016/0361-9230(90)90158-v.

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15

Cansino, Selene, Samuel J. Williamson, and Daniel Karron. "Tonotopic organization of human auditory association cortex." Brain Research 663, no. 1 (1994): 38–50. http://dx.doi.org/10.1016/0006-8993(94)90460-x.

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16

Neafsey, E. J. "The concept of association cortex should be abandoned." Behavioral and Brain Sciences 11, no. 1 (1988): 97. http://dx.doi.org/10.1017/s0140525x00052924.

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17

Murakami, Kunio, and Kiyoshi Kishi. "Analaysis of association fibers of piriform cortex neurons." Neuroscience Research Supplements 14 (January 1991): S55. http://dx.doi.org/10.1016/s0921-8696(06)80153-2.

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18

Yeo, B. T. Thomas, Fenna M. Krienen, Simon B. Eickhoff, et al. "Functional Specialization and Flexibility in Human Association Cortex." Cerebral Cortex 25, no. 10 (2014): 3654–72. http://dx.doi.org/10.1093/cercor/bhu217.

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19

Yeo, B. T. Thomas, Fenna M. Krienen, Simon B. Eickhoff, et al. "Functional Specialization and Flexibility in Human Association Cortex." Cerebral Cortex 26, no. 1 (2015): 465. http://dx.doi.org/10.1093/cercor/bhv260.

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20

Herbert, Martha R., Gordon J. Harris, Kristen T. Adrien, et al. "Abnormal asymmetry in language association cortex in autism." Annals of Neurology 52, no. 5 (2002): 588–96. http://dx.doi.org/10.1002/ana.10349.

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21

Passingham, R. E. "Cerebral cortex, vol. 4, association and auditory cortices." Neuroscience 21, no. 3 (1987): 1023. http://dx.doi.org/10.1016/0306-4522(87)90057-1.

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22

Tanaka, Masafumi. "Afferent connections of the prelunate visual association cortex." Neuroscience Research Supplements 15 (January 1990): S143. http://dx.doi.org/10.1016/0921-8696(90)90459-g.

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23

Tanaka, Masafumi. "Afferent connections of the prelunate visual association cortex." Neuroscience Research Supplements 11 (January 1990): S143. http://dx.doi.org/10.1016/0921-8696(90)90882-4.

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24

Rolls, E. T., H. D. Critchley, R. Mason, and E. A. Wakeman. "Orbitofrontal cortex neurons: role in olfactory and visual association learning." Journal of Neurophysiology 75, no. 5 (1996): 1970–81. http://dx.doi.org/10.1152/jn.1996.75.5.1970.

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1. The orbitofrontal cortex is implicated in the rapid learning of new associations between visual stimuli and primary reinforcers such as taste. It is also the site of convergence of information from olfactory, gustatory, and visual modalities. To investigate the neuronal mechanisms underlying the formation of odor-taste associations, we made recordings from olfactory neurons in the orbitofrontal cortex during the performance of an olfactory discrimination task and its reversal in macaques. 2. It was found that 68% of odor-responsive neurons modified their responses after the changes in the taste reward associations of the odorants. Full reversal of the neuronal responses was seen in 25% of these neurons. Extinction of the differential neuronal responses after task reversal was seen in 43% of these neurons. 3. For comparison, visually responsive orbitofrontal neurons were tested during reversal of a visual discrimination task. Seventy-one percent of these visual cells showed rapid full reversal of the visual stimulus to which they responded, when the association of the visual with taste was reversed in the reversal task. 4. These demonstrate that of many orbitofrontal cortex olfactory neurons on the taste with which the odor is associated. 5. This modification is likely to be important for setting the motivational value of olfactory for feeding and other rewarded behavior. However, it is less complete, and much slower, than the modifications found or orbit frontal visual during visual-taste reversal. This relative inflexibility of olfactory responses is consistent with the need for some stability is odor-taste associations to facilitate the formation and perception of flavors.

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25

Turner, G. R., A. J. Chen, J. Hoffman, and M. D'Esposito. "Dorsolateral prefrontal cortex lesions impair goal-directed modulation of representations within visual association cortex." NeuroImage 47 (July 2009): S190. http://dx.doi.org/10.1016/s1053-8119(09)72126-3.

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26

R, Ramani, Qiu M, Shulman RG, Hyder F, and Constable RT. "Sevoflurane 0.25 MAC Affects Association Cortex More Than Primary Cortex - fMRI Study in Volunteers." Journal of Neurosurgical Anesthesiology 17, no. 4 (2005): 242–43. http://dx.doi.org/10.1097/01.ana.0000187752.71537.c3.

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27

Sawada, Kaori, Shigehiro Miyachi, Akiko Yamashita, et al. "Organization of Multisynaptic Inputs from the Parietal Association Cortex to the Primary Motor Cortex." Journal of Nihon University Medical Association 67, no. 2 (2008): 115–22. http://dx.doi.org/10.4264/numa.67.115.

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28

Yukie, Masao. "Neural connections of auditory association cortex with the posterior cingulate cortex in the monkey." Neuroscience Research 22, no. 2 (1995): 179–87. http://dx.doi.org/10.1016/0168-0102(95)00888-1.

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29

Sweet, Robert A., Ronald L. Hamilton, Oscar L. Lopez, et al. "Psychotic Symptoms in Alzheimer's Disease Are Not Associated With More Severe Neuropathologic Features." International Psychogeriatrics 12, no. 4 (2000): 547–58. http://dx.doi.org/10.1017/s1041610200006657.

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Psychotic symptoms in Alzheimer's disease (AD) have been associated with increased rates of cognitive impairment and functional decline. Prior studies have been conflicting with regard to whether AD patients with psychosis (AD+P) have evidence of more severe neuropathologic findings at postmortem exam. We examined the severity of neuritic plaques and neurofibrillary tangles in six brain regions—middle frontal cortex, hippocampus, inferior parietal cortex, superior temporal cortex, occipital cortex, and transentorhinal cortex—in 24 AD+P subjects and 25 matched AD subjects without psychosis (AD-P). All analyses controlled for the presence of cortical Lewy bodies, and corrected for multiple comparisons. We found no significant associations between neuritic plaque and neurofibrillary tangle severity and AD+P, and no significant associations with any individual psychotic symptom. The association of AD+P with a more rapidly progressive course of AD appears to be mediated by a neuropathologic process other than increased severity of plaque and tangle formation.

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30

Choi, Eun Young, Garrett K. Drayna, and David Badre. "Evidence for a Functional Hierarchy of Association Networks." Journal of Cognitive Neuroscience 30, no. 5 (2018): 722–36. http://dx.doi.org/10.1162/jocn_a_01229.

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Patient lesion and neuroimaging studies have identified a rostral-to-caudal functional gradient in the lateral frontal cortex (LFC) corresponding to higher-order (complex or abstract) to lower-order (simple or concrete) cognitive control. At the same time, monkey anatomical and human functional connectivity studies show that frontal regions are reciprocally connected with parietal and temporal regions, forming parallel and distributed association networks. Here, we investigated the link between the functional gradient of LFC regions observed during control tasks and the parallel, distributed organization of association networks. Whole-brain fMRI task activity corresponding to four orders of hierarchical control [Badre, D., & D'Esposito, M. Functional magnetic resonance imaging evidence for a hierarchical organization of the prefrontal cortex. Journal of Cognitive Neuroscience, 19, 2082–2099, 2007] was compared with a resting-state functional connectivity MRI estimate of cortical networks [Yeo, B. T., Krienen, F. M., Sepulcre, J., Sabuncu, M. R., Lashkari, D., Hollinshead, M., et al. The organization of the human cerebral cortex estimated by intrinsic functional connectivity. Journal of Neurophysiology, 106, 1125–1165, 2011]. Critically, at each order of control, activity in the LFC and parietal cortex overlapped onto a common association network that differed between orders. These results are consistent with a functional organization based on separable association networks that are recruited during hierarchical control. Furthermore, corticostriatal functional connectivity MRI showed that, consistent with their participation in functional networks, rostral-to-caudal LFC and caudal-to-rostral parietal regions had similar, order-specific corticostriatal connectivity that agreed with a striatal gating model of hierarchical rule use. Our results indicate that hierarchical cognitive control is subserved by parallel and distributed association networks, together forming multiple localized functional gradients in different parts of association cortex. As such, association networks, while connectionally organized in parallel, may be functionally organized in a hierarchy via dynamic interaction with the striatum.

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31

Lowe, Val J., Tyler J. Bruinsma, Heather J. Wiste, et al. "Cross-sectional associations of tau-PET signal with cognition in cognitively unimpaired adults." Neurology 93, no. 1 (2019): e29-e39. http://dx.doi.org/10.1212/wnl.0000000000007728.

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ObjectiveTo assess cross-sectional associations of neurofibrillary tangles, measured by tau-PET, with cognitive performance in cognitively unimpaired (CU) adults.MethodsTau- and amyloid-PET were performed in 579 CU participants aged 50–98 from the population-based Mayo Clinic Study of Aging. Associations between tau-PET signal in 43 brain regions and cognitive test scores were assessed using penalized linear regression. In additional models, participants were classified by normal/abnormal global amyloid-PET (A+/A−) and normal/abnormal regional tau-PET (T+/T−). Regional tau-PET cutpoints were defined as standardized uptake value ratio (SUVR) greater than the 95th percentile of tau-PET SUVR in that region among 117 CU participants aged 30–49.ResultsHigher tau-PET signal was associated with poorer memory performance in all medial temporal lobe (MTL) regions and also in the middle temporal pole and frontal olfactory regions. The largest association with tau-PET and memory z scores was seen in the entorhinal cortex; this association was independent of tau-PET signal in other brain regions. Tau-PET in the entorhinal cortex was also associated with poorer global and language performance. In the entorhinal cortex, T+ was associated with lower memory performance among both A− and A+.ConclusionsTau deposition in MTL regions, as reflected by tau-PET signal, was associated with poorer performance on memory tests in CU participants. The association with entorhinal cortex tau-PET was independent of tau-PET signal in other brain regions. Longitudinal studies are needed to understand the fate of CU participants with elevated medial temporal tau-PET signal.

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32

Critchley, H. D., and E. T. Rolls. "Olfactory neuronal responses in the primate orbitofrontal cortex: analysis in an olfactory discrimination task." Journal of Neurophysiology 75, no. 4 (1996): 1659–72. http://dx.doi.org/10.1152/jn.1996.75.4.1659.

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1.The primate orbitofrontal cortex receives inputs from the primary olfactory (pyriform) cortex and also from the primary taste cortex. To investigate how olfactory information is encoded in the orbitofrontal cortex, the responses of single neurons in the orbitofrontal cortex and surrounding areas were recorded during the performance of an olfactory discrimination task. In the task, the delivery of one of eight different odors indicated that the monkey could lick to obtain a taste of sucrose. If one of two other odors was delivered from the olfactometer, the monkey had to refrain from licking, otherwise he received a taste of saline. 2. Of the 1,580 neurons recorded in the orbitofrontal cortex, 3.1% (48) had olfactory responses and 34 (2.2%) responded differently to the different odors in the task. The neurons responded with a typical latency of 180 ms from the onset of odorant delivery. 3. Of the olfactory neurons with differential responses in the task, 35% responded solely on the basis of the taste reward association of the odorants. Such neurons responded either to all the rewarded stimuli, and none of the saline-associated stimuli, or vice versa. 4. The remaining 65% of these neurons showed differential selectivity for the stimuli based on the odor quality and not on the taste reward association of the odor. 5. The findings show that the olfactory representation within the orbitofrontal cortex reflects for some neurons (65%) which odor is present independently of its association with taste reward, and that for other neurons (35%), the olfactory response reflects (and encodes) the taste association of the odor. The additional finding that some of the odor-responsive neurons were also responsive to taste stimuli supports the hypothesis that odor-taste association learning at the level of single neurons in the orbitofrontal cortex enables such cells to show olfactory responses that reflect the taste association of the odor.

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33

Gutiérrez-Galve, Leticia, Stefania Bruno, Claudia A. M. Wheeler-Kingshott, Mary Summers, Lisa Cipolotti, and Maria A. Ron. "IQ and the Fronto-temporal Cortex in Bipolar Disorder." Journal of the International Neuropsychological Society 18, no. 2 (2012): 370–74. http://dx.doi.org/10.1017/s1355617711001706.

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AbstractCognitive changes are documented in bipolar disorder (BP). Cortical volume loss, especially in prefrontal regions, has also been reported, but associations between cognition and cortical abnormalities have not been fully documented. This study explores associations between cognitive performance and cortical parameters (area, thickness and volume) of the fronto-temporal cortex in 36 BP patients (25 BPI and 11 BPII). T1-weighted volumetric MRI images were obtained using a 1.5 Tesla scanner. Cortical parameters were measured using surface-based morphometry and their associations with estimated premorbid, current IQ, visual memory, and executive function explored. Premorbid IQ was associated with frontal cortical area and volume, but no such associations were present for current cognitive performance. Cortical parameters were not different in BPI and BPII patients, but the association between current IQ and temporal cortical area was stronger in BPII patients. The pattern of cortico-cognitive associations in BPI and BPII patients merits further consideration. (JINS, 2012, 18, 370–374)

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Nagai, M., K. Kishi, and S. Kato. "Insular cortex and neuropsychiatric disorders: A review of recent literature." European Psychiatry 22, no. 6 (2007): 387–94. http://dx.doi.org/10.1016/j.eurpsy.2007.02.006.

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AbstractThe insular cortex is located in the centre of the cerebral hemisphere, having connections with the primary and secondary somatosensory areas, anterior cingulate cortex, amygdaloid body, prefrontal cortex, superior temporal gyrus, temporal pole, orbitofrontal cortex, frontal and parietal opercula, primary and association auditory cortices, visual association cortex, olfactory bulb, hippocampus, entorhinal cortex, and motor cortex. Accordingly, dense connections exist among insular cortex neurons. The insular cortex is involved in the processing of visceral sensory, visceral motor, vestibular, attention, pain, emotion, verbal, motor information, inputs related to music and eating, in addition to gustatory, olfactory, visual, auditory, and tactile data. In this article, the literature on the relationship between the insular cortex and neuropsychiatric disorders was summarized following a computer search of the Pub-Med database. Recent neuroimaging data, including voxel based morphometry, PET and fMRI, revealed that the insular cortex was involved in various neuropsychiatric diseases such as mood disorders, panic disorders, PTSD, obsessive-compulsive disorders, eating disorders, and schizophrenia. Investigations of functions and connections of the insular cortex suggest that sensory information including gustatory, olfactory, visual, auditory, and tactile inputs converge on the insular cortex, and that these multimodal sensory information may be integrated there.

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35

Yan, Jun. "CANADIAN ASSOCIATION OF NEUROSCIENCE REVIEW: Development and Plasticity of the Auditory Cortex." Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques 30, no. 3 (2003): 189–200. http://dx.doi.org/10.1017/s0317167100002572.

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ABSTRACT:The functions of the cerebral cortex are predominantly established during the critical period of development. One obvious developmental feature is its division into different functional areas that systematically represent different environmental information. This is the result of interactions between intrinsic (genetic) factors and extrinsic (environmental) factors. Following this critical period, the cerebral cortex attains its adult form but it will continue to adapt to environmental changes. Thus, the cerebral cortex is constantly adapting to the environment (plasticity) from its embryonic stages to the last minute of life. This review details important factors that contribute to the development and plasticity of the auditory cortex. The instructive role of thalamocortical innervation, the regulatory role of cholinergic projection of the basal forebrain and the potential role of the corticofugal modulation are presented.

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36

Couldwell, William T. "Tomita H, Ohbayashi M, Nakahara K, Hasegawa I, Miyashita Y." Neurosurgical Focus 7, no. 6 (1999): E14. http://dx.doi.org/10.3171/foc.1999.7.6.15.

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Knowledge or experience is voluntarily recalled from memory by reactivation of the neural representations in the cerebral association cortex. In inferior temporal cortex, which serves as the storehouse of visual long-term memory, activation of mnemonic engrams through electric stimulation results in imagery recall in humans, and neurons can be dynamically activated by the necessity for memory recall in monkeys. Neuropsychological studies and previous split-brain experiments predicted that prefrontal cortex exerts executive control upon inferior temporal cortex in memory retrieval; however, no neuronal correlate of this process has ever been detected. Here we show evidence of the top-down signal from prefrontal cortex. In the absence of bottom-up visual inputs, single inferior temporal neurons were activated by the top-down signal, which conveyed information on semantic categorization imposed by visual stimulus-stimulus association. Behavioural performance was severely impaired with loss of the top-down signal. Control experiments confirmed that the signal was transmitted not through a subcortical but through a fronto-temporal cortical pathway. Thus, feedback projections from prefrontal cortex to the posterior association cortex appear to serve the executive control of voluntary recall.

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37

Schoenbaum, G., and H. Eichenbaum. "Information coding in the rodent prefrontal cortex. I. Single-neuron activity in orbitofrontal cortex compared with that in pyriform cortex." Journal of Neurophysiology 74, no. 2 (1995): 733–50. http://dx.doi.org/10.1152/jn.1995.74.2.733.

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1. Extracellular spike activity was recorded from 1,942 single neurons in orbitofrontal cortex (OF) and 591 single neurons in pyriform cortex (PIR) over multiple sessions in rats performing an eight-odor discrimination task in which the stimulus sequence contained predictable associations between particular odor pairs. Neural firing patterns were examined in relation to task events in the current trial and variables associated with current sensory processing, events of recent past trials, and long-term associations involving the odor cues. 2. Overall, 34% of single neurons in OF and 30% of single neurons in PIR fired selectively during one or more salient trial events including trial initiation, odor sampling, performance of the discriminative response, and water consumption. The activity of other cells recorded in OF (13%) and PIR (10%) was suppressed for the duration of each trial. Although the proportion of some cell types differed between the two areas, the firing patterns of OF and PIR neurons were qualitatively indistinguishable. 3. Firing during odor sampling and the discriminative response was influenced by the identity of the current odor. Some cells fired selectively to a single odor, but most cells were coarsely tuned such that they fired to several of the eight odors to differing degrees consistent with previous reports. Considerable odor coding was observed in both OF and PIR. 4. Firing during trial initiation and odor sampling was also influenced by the identity and reward association of the odor presented in the immediately preceding trial. The influence of past odor identity and valence was observed in both OF and PIR. 5. Firing during trial events was also influenced by the acquired associations between odors and their assigned reward contingencies and between pairs of odors involved in predictive relationships. The reward valence of the current odor significantly influenced firing during odor sampling and the discriminative response; some cells responded preferentially to rewarded odors and others to nonrewarded odors. Firing during trial initiation and odor sampling reflected whether or not the odor in the current trial had been predicted by the odor in the preceding trial. In addition, firing during odor sampling reflected the expectation of reward in the following trial that could be inferred from the predictable associations between odors. Each of these properties was observed in both OF and PIR. 6. The findings in OF were consistent with the view that prefrontal subdivisions mediate the temporal organization of complex behaviors within specific informational domains. OF appears to be concerned with the specific domain of olfaction.(ABSTRACT TRUNCATED AT 400 WORDS)

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Wu, Dongya, Lingzhong Fan, Ming Song, et al. "Hierarchy of Connectivity–Function Relationship of the Human Cortex Revealed through Predicting Activity across Functional Domains." Cerebral Cortex 30, no. 8 (2020): 4607–16. http://dx.doi.org/10.1093/cercor/bhaa063.

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Abstract Many studies showed that anatomical connectivity supports both anatomical and functional hierarchies that span across the primary and association cortices in the cerebral cortex. Even though a structure–function relationship has been indicated to uncouple in the association cortex, it is still unknown whether anatomical connectivity can predict functional activations to the same degree throughout the cortex, and it remains unclear whether a hierarchy of this connectivity–function relationship (CFR) exists across the human cortex. We first addressed whether anatomical connectivity could be used to predict functional activations across different functional domains using multilinear regression models. Then, we characterized the CFR by predicting activity from anatomical connectivity throughout the cortex. We found that there is a hierarchy of CFR between sensory–motor and association cortices. Moreover, this CFR hierarchy was correlated to the functional and anatomical hierarchies, respectively, reflected in functional flexibility and the myelin map. Our results suggest a shared hierarchical mechanism in the cortex, a finding which provides important insights into the anatomical and functional organizations of the human brain.

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Kawasaki, Keisuke, and David L. Sheinberg. "Learning to Recognize Visual Objects With Microstimulation in Inferior Temporal Cortex." Journal of Neurophysiology 100, no. 1 (2008): 197–211. http://dx.doi.org/10.1152/jn.90247.2008.

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The malleability of object representations by experience is essential for adaptive behavior. It has been hypothesized that neurons in inferior temporal cortex (IT) in monkeys are pivotal in visual association learning, evidenced by experiments revealing changes in neural selectivity following visual learning, as well as by lesion studies, wherein functional inactivation of IT impairs learning. A critical question remaining to be answered is whether IT neuronal activity is sufficient for learning. To address this question directly, we conducted experiments combining visual classification learning with microstimulation in IT. We assessed the effects of IT microstimulation during learning in cases where the stimulation was exclusively informative, conditionally informative, and informative but not necessary for the classification task. The results show that localized microstimulation in IT can be used to establish visual classification learning, and the same stimulation applied during learning can predictably bias judgments on subsequent recognition. The effect of induced activity can be explained neither by direct stimulation-motor association nor by simple detection of cortical stimulation. We also found that the learning effects are specific to IT stimulation as they are not observed by microstimulation in an adjacent auditory area. Our results add the evidence that the differential activity in IT during visual association learning is sufficient for establishing new associations. The results suggest that experimentally manipulated activity patterns within IT can be effectively combined with ongoing visually induced activity during the formation of new associations.

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40

Kajiwara, Riichi, Ichiro Takashima, Yuka Mimura, Menno P. Witter, and Toshio Iijima. "Amygdala Input Promotes Spread of Excitatory Neural Activity From Perirhinal Cortex to the Entorhinal–Hippocampal Circuit." Journal of Neurophysiology 89, no. 4 (2003): 2176–84. http://dx.doi.org/10.1152/jn.01033.2002.

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A number of sensory modalities most likely converge in the rat perirhinal cortex. The perirhinal cortex also interconnects with the amygdala, which plays an important role in various motivational and emotional behaviors. The neural pathway from the perirhinal cortex to the entorhinal cortex is considered one of the main paths into the entorhinal–hippocampal network, which has a crucial role in memory processes. To investigate the potential associative function of the perirhinal cortex with respect to sensory and motivational stimuli and the influence of the association on the perirhinal–entorhinal–hippocampal neurocircuit, we prepared rat brain slices including the perirhinal cortex, entorhinal cortex, hippocampal formation, and amygdala. We used an optical imaging technique with a voltage-sensitive dye to analyze 1) the spatial and functional distribution of inputs from the lateral nucleus of the amygdala to the perirhinal cortex; 2) the spread of neural activity in the perirhinal cortex after layers II/III stimulation, which mimics sensory input to the perirhinal cortex; and 3) the effect of associative inputs to the perirhinal cortex from both the lateral amygdaloid nucleus and layers II/III of the perirhinal cortex on the perirhinal–entorhinal–hippocampal neurocircuit. Following stimulation in the superficial layers of the perirhinal cortex, electrical activity only propagated into the entorhinal cortex when sufficient activation occurred in the deep layers of perirhinal area 35. We observed that single stimulation of either the perirhinal cortex or amygdala did not result in sufficient neural activation of the deep layers of areas 35 to provoke activity propagation into the entorhinal cortex. However, the deep layers of area 35 were depolarized much more strongly when the two stimuli were applied simultaneously, resulting in spreading activation in the entorhinal cortex. Our observations suggest that a functional neural basis for the association of higher-order sensory inputs and emotion-related inputs exists in the perirhinal cortex and that transfer of sensory information to the entorhinal–hippocampal circuitry might be affected by the association of that information with incoming information from the amygdala.

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Zhang, Carey Y., Tyson Aflalo, Boris Revechkis, et al. "Partially Mixed Selectivity in Human Posterior Parietal Association Cortex." Neuron 95, no. 3 (2017): 697–708. http://dx.doi.org/10.1016/j.neuron.2017.06.040.

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Brigell, Mitchell, Antonio Strafella, and Gastone Celesia. "Processing of color and luminance in visual association cortex." NeuroImage 3, no. 3 (1996): S266. http://dx.doi.org/10.1016/s1053-8119(96)80268-0.

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Rauschecker, Josef P., and Biao Tian. "Processing of “what” and “where” in auditory association cortex." International Congress Series 1250 (October 2003): 37–51. http://dx.doi.org/10.1016/s0531-5131(03)00191-2.

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Buchanan, Robert W., Alan Francis, Celso Arango, et al. "Morphometric Assessment of the Heteromodal Association Cortex in Schizophrenia." American Journal of Psychiatry 161, no. 2 (2004): 322–31. http://dx.doi.org/10.1176/appi.ajp.161.2.322.

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Dahl, C. D., N. K. Logothetis, and C. Kayser. "Spatial Organization of Multisensory Responses in Temporal Association Cortex." Journal of Neuroscience 29, no. 38 (2009): 11924–32. http://dx.doi.org/10.1523/jneurosci.3437-09.2009.

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Aylward, Alana, Priscilla Auduong, Jeffrey S. Anderson, et al. "Changes in the Auditory Association Cortex in Dementing Illnesses." Otology & Neurotology 41, no. 10 (2020): 1327–33. http://dx.doi.org/10.1097/mao.0000000000002786.

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David, Anthony S., Peter W. R. Woodruff, Robert Howard, et al. "Auditory hallucinations inhibit exogenous activation of auditory association cortex." NeuroReport 7, no. 4 (1996): 932–36. http://dx.doi.org/10.1097/00001756-199603220-00021.

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Berry, I., J.-F. Démonet, S. Warach, et al. "Activation of Association Auditory Cortex Demonstrated with Functional MRI." NeuroImage 2, no. 3 (1995): 215–19. http://dx.doi.org/10.1006/nimg.1995.1028.

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Moniruzzaman, Mohammad, Aya Kadota, Akihiko Shiino, et al. "Seven-Day Pedometer-Assessed Step Counts and Brain Volume: A Population-Based Observational Study." Journal of Physical Activity and Health 18, no. 2 (2021): 157–64. http://dx.doi.org/10.1123/jpah.2019-0659.

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Background: To investigate the association between step counts and brain volumes (BVs)—global and 6 a priori selected cognition-related regions of interest—in Japanese men aged 40–79 years. Methods: The authors analyzed data from 680 cognitively intact participants of the Shiga Epidemiological Study of Subclinical Atherosclerosis—a population-based observational study. Using multivariable linear regression, the authors assessed cross-sectional associations between 7-day step counts at baseline (2006–2008) and BVs at follow-up (2012–2015) for age-stratified groups (<60 y and ≥60 y). Results: In the older adults ≥60 years, step counts at baseline (per 1000 steps) were associated with total BV at follow-up (β = 1.42, P = .022) while adjusted for potential covariates. Regions of interest-based analyses yielded an association of step counts with both prefrontal cortexes (P < .05) in older adults, while the left entorhinal cortex showed marginally significant association (P = .05). No association was observed with hippocampus, parahippocampal, cingulum, and cerebellum. No association was observed in younger adults (<60 y). Conclusions: The authors found a positive association between 7-day step counts and BVs, including prefrontal cortexes, and left entorhinal cortex in apparently healthy Japanese men.

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Cromer, Jason A., Michelle Machon, and Earl K. Miller. "Rapid Association Learning in the Primate Prefrontal Cortex in the Absence of Behavioral Reversals." Journal of Cognitive Neuroscience 23, no. 7 (2011): 1823–28. http://dx.doi.org/10.1162/jocn.2010.21555.

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The PFC plays a central role in our ability to learn arbitrary rules, such as “green means go.” Previous experiments from our laboratory have used conditional association learning to show that slow, gradual changes in PFC neural activity mirror monkeys' slow acquisition of associations. These previous experiments required monkeys to repeatedly reverse the cue–saccade associations, an ability known to be PFC-dependent. We aimed to test whether the relationship between PFC neural activity and behavior was due to the reversal requirement, so monkeys were trained to learn several new conditional cue–saccade associations without reversing them. Learning-related changes in PFC activity now appeared earlier and more suddenly in correspondence with similar changes in behavioral improvement. This suggests that learning of conditional associations is linked to PFC activity regardless of whether reversals are required. However, when previous learning does not need to be suppressed, PFC acquires associations more rapidly.

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