Where can i find pictures of the human brain

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  2. Memories, Photographs, and the Human Brain
  3. human brain images
  4. 279 513 human brain stock photos, vectors, and illustrations are available royalty-free.

This levels effect is greater for words than for pictures because of superior picture memory even after shallow or nonsemantic encoding 6. One theory of the mechanism underlying superior picture memory is that pictures automatically engage multiple representations and associations with other knowledge about the world, thus encouraging a more elaborate encoding than occurs with words 2 , 5 , 7.

This theory implies that there are qualitative differences between the ways words and pictures are processed during memory. However, the brain mechanisms underlying this phenomenon are not well understood. Neuroimaging experiments using verbal or nonverbal materials as stimuli have suggested that there are differences in the brain areas participating in the processing of these two kinds of stimulus. For example, previous neuroimaging experiments have shown medial temporal activation during encoding of faces and other nonverbal visual stimuli 8 — 13 , but not consistently during encoding of words 14 — Conversely, activation of medial temporal areas has been found during word retrieval 17 , 18 , but not consistently during retrieval of nonverbal material 10 , 11 , 19 , A comparison of recall for words and pictures failed to find any difference between them, but because recall of the name corresponding to the picture also was required, differences between the two conditions may have been reduced These results suggest differences between the functional neuroanatomy for word and picture memory, but sufficient direct comparisons are lacking.

We examined the neural correlates of memory for pictures and words in the context of memory encoding to determine whether material-specific brain networks for memory could be identified. In addition, encoding was carried out under three different sets of instructions to see whether material specificity is a general property of memory or is dependent on how the material is processed. An additional 12 subjects participated in a pilot experiment, and their data have been included in the behavioral analysis.

The stimuli used in the experiment were concrete, high-frequency words or line drawings of familiar objects All stimuli were presented on a computer monitor in black with a white background. There were three encoding tasks for both words and pictures, requiring three lists of pictures and three lists of words. All lists were matched for word frequency, word length, familiarity, and complexity of the picture regardless of whether the list was presented as words or pictures. For two of the encoding conditions, subjects were instructed to make certain decisions about the stimuli, but were not explicitly asked to remember them; memory for items presented during these conditions therefore was incidental.

These two conditions were chosen because previous work has shown that information that has been processed during deep encoding, i. During the third condition, intentional learning, subjects were instructed to memorize the pictures or words and were told that they would be tested on these items. After the scans, subjects completed two recognition memory tasks, one for stimuli encoded as words and one for stimuli encoded as pictures. These tasks consisted of 10 targets from each of the three encoding conditions for words or pictures and 30 distracters i.

All stimuli in the recognition tasks were presented as words, regardless of whether they originally were presented as words or pictures, to prevent ceiling effects for picture recognition. Six positron emission tomography scans, with injections of 40 mCi of H 2 15 O each and separated by 11 min, were performed on all subjects while they were encoding the stimuli described above.

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This tomograph allows 15 planes, separated by 6. Emission data were corrected for attenuation by means of a transmission scan obtained at the same levels as the emission scans. Each task started 20 sec before isotope injection and continued throughout the 1-min scanning period. For the six scans, the three lists were assigned to the three encoding conditions in a counterbalanced fashion, and the order of conditions also was counterbalanced across subjects.

Memories, Photographs, and the Human Brain

During all scans subjects pressed a button with the right index or middle finger to either indicate their decisions about the stimulus or, during the intentional learning condition, to simply make a motor response. Behavioral data were analyzed by using a repeated measures ANOVA with stimulus type and encoding condition as the repeated measures.

Positron emission tomography scans were registered by using air 23 , and spatially normalized to the Talairach and Tournoux atlas coordinate system, ref. Ratios of regional cerebral blood flow rCBF to global cerebral blood flow CBF within each scan for each subject were computed and analyzed by using partial least squares PLS 26 to identify spatially distributed patterns of brain activity related to the different task conditions.

PLS is a multivariate analysis that operates on the covariance between brain voxels and the experimental design to identify a new set of variables so-called latent variables or LVs that optimally relate the two sets of measurements. We used PLS to analyze the covariance of brain voxel values with orthonormal contrasts coding for the experimental design.

The outcome is sets of mutually independent spatial activity patterns depicting the brain regions that, as a whole, show the strongest relation to i. These patterns are displayed as singular images Fig. Each brain voxel has a weight, known as a salience, that is proportional to these covariances, and multiplying the rCBF value in each brain voxel for each subject by the salience for that voxel, and summing across all voxels gives a score for each subject on a given LV. The significance for each LV as a whole was assigned by using a permutation test 26 , The first three LVs identified brain regions associated with the main effects of stimulus type and encoding condition, and the fourth and fifth LVs identified interactions between stimulus type and encoding condition.

Because saliences are derived in a single analytic step, no correction for multiple comparisons of the sort done for univariate image analyses is required. Voxels shown in color are those that best characterize the patterns of activity identified by LVs 1—3 from the PLS analysis see Materials and Methods.

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Numbers shown on the left indicate the level in mm of the. In addition to the permutation test, a second and independent step in PLS analysis is to determine the stability of the saliences for the brain voxels characterizing each pattern identified by the LVs. To do this, all saliences were submitted to a bootstrap estimation of the standard errors 28 , This estimation involves randomly resampling subjects, with replacement, and computing the standard error of the saliences after a sufficient number of bootstrap samples.

Locations of these maxima are reported in terms of brain region, or gyrus, and Brodmann area BA as defined in the Talairach and Tournoux atlas. Selected local maxima are shown in Tables 2 and 3 , with the results of corresponding contrasts from SPM95 i. Univariate tests were performed on selected maxima as an adjunct to the PLS analysis to aid in the interpretation of interaction effects, not as a test of significance.

The inferential component of our analysis comes from the permutation test and the reliability assessed through the bootstrap estimates. Pictures were remembered better than words overall Table 1 , and both semantic processing and intentional learning resulted in better recognition than nonsemantic encoding.

In addition, there was a significant interaction of stimulus type and encoding strategy on recognition performance, caused by a larger difference between memory for pictures and words during the nonsemantic condition. The right side of the image represents the right side of the brain. A Brain areas with increased rCBF during encoding of pictures are shown in yellow and red, and areas with increased activity during encoding of words are shown in blue LV1.

B Brain areas with increased rCBF during semantic encoding, compared with the other two conditions LV2 , are shown in red. C Brain areas with increased rCBF during intentional learning, compared with the other two conditions LV3 , are shown in red. Selected maxima from these regions are shown in Table 2. Three patterns of rCBF activity predominantly related to the main effects of stimulus type and encoding condition were identified.

One pattern distinguished encoding of pictures from that of words, one characterized semantic encoding from nonsemantic processing and intentional learning, and a third dissociated intentional learning from the other two conditions. There was greater activation during encoding of pictures, compared with words, in a widespread area of bilateral ventral and dorsal extrastriate cortex, and in bilateral medial temporal cortex, particularly the ventral portion Fig. In both of these regions the increase in rCBF was more extensive in the right hemisphere.

In extrastriate cortex, rCBF was increased during picture encoding over word encoding equally across all three encoding strategy conditions, whereas in medial temporal cortex this stimulus-specific difference was greater during the nonsemantic processing condition Fig. Encoding of words, on the other hand, was associated with greater rCBF across all conditions in bilateral prefrontal cortex and anterior portions of middle temporal cortex Fig. In contrast to the rCBF increases during picture encoding, the increases in prefrontal and temporal cortices during word encoding were more extensive in the left hemisphere.

Increased rCBF also was found in left parietal cortex during encoding of words. Selected cortical areas with differential activity during encoding: Main effects.

Ratios of rCBF to whole brain CBF in areas of the brain that showed interactions between stimulus type and encoding condition. The brain regions with increased activity during the semantic encoding condition, compared with the other two conditions, were mainly in the left hemisphere. These regions included ventral and dorsal portions of medial prefrontal cortex, and an area that included both the medial temporal region and the posterior portion of the insula Fig.

Semantic encoding also led to an increase of rCBF in bilateral posterior extrastriate cortex. This pattern of rCBF increase during semantic encoding was found for both pictures and words. Increased rCBF during intentional learning, compared with both incidental encoding conditions, also was seen in left prefrontal cortex, but in left ventrolateral prefrontal cortex, in contrast to the medial and anterior areas activated during semantic encoding Fig.

In addition, increased rCBF was found in left premotor cortex and caudate nucleus, and in bilateral ventral extrastriate cortex during intentional learning. As was the case with semantic encoding, the rCBF pattern seen in these regions during intentional learning characterized both pictures and words. There were a few brain regions that showed an interaction between stimulus type and encoding condition Table 3 , particularly the medial temporal regions.


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In addition to the difference already noted in these areas during nonsemantic encoding, there was another region in right medial temporal cortex that showed an interaction involving the nonsemantic and intentional learning conditions identified on LV4. This interaction was caused by sustained activity in this region across the picture encoding conditions, with a reduction in activity during intentional learning of words compared with the nonsemantic condition Fig.

There also was an area in the left medial temporal cortex that showed the opposite interaction, consisting of a larger increase in activity during learning of words, compared with the nonsemantic condition Fig. Finally, there was an interaction in left motor cortex identified on LV5 caused by an increase in activity in the semantic condition for pictures, compared with the nonsemantic condition, with the opposite pattern for words Fig. Conversely, there was an increase in activity during semantic encoding in left orbitofrontal cortex, but only for words Fig.

Selected cortical areas with differential activity during encoding: Interactions.


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The results of this experiment address three questions about the neurobiology of memory, the first of which is why pictures are remembered better than words. The behavioral results showed a general difference in recognition accuracy between pictures and words that was greatest on those items that had been processed via nonsemantic encoding. The brain activity measures identified regions that showed a general pattern of differences between pictures and words, as well as regions that had differences mainly during nonsemantic processing. Increased rCBF during the picture-encoding conditions was found in bilateral extrastriate and ventral medial temporal cortices.

Extrastriate cortex is activated during the visual perception of both verbal and nonverbal material 30 — 33 and may have been more active during picture encoding because the pictures, although simple line drawings, were probably more visually complex than the words.

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This difference in visual characteristics could have influenced medial temporal activity as well. On the other hand, medial temporal cortex has long been known from lesion experiments to be important for episodic memory 34 — 38 and may be particularly important for encoding new information The greater activity in medial temporal cortex during encoding of pictures compared with words suggests that pictures more directly or effectively engage these memory-related regions in the brain, thereby resulting in superior recollection of these items.

This effect may be related in part to distinctiveness or novelty, which has been shown to activate medial temporal cortex 13 , considering that the pictures, even though they were of familiar objects, might be more novel than familiar words. In addition, because better memory for pictures and activation of medial temporal cortex both were more evident in the nonsemantic encoding condition, engagement of memory networks by pictures may be automatic and result in more durable memory traces Therefore, this type of information is apparently better represented and more readily accessible to retrieval mechanisms, regardless of the ostensible encoding task.

Words, on the other hand, activate left hemisphere regions previously shown to be involved in language tasks, including left frontal, temporal, and parietal regions 30 , 41 , This result implies that encoding of words primarily invokes a distributed system of regions involved in linguistic processing that is less able to support later retrieval from episodic memory.

The Human Brain

William Utermohlen self-portrait After being diagnosed with Alzheimer's disease in , American artist William Utermohlen chronicled his descent into dementia through a series of powerful self-portraits drawn over 12 years. He started painting this oil on canvas, "Self Portrait with Saw," in , on the day he willed his brain to science. Utermohlen died in in his seventies.

279 513 human brain stock photos, vectors, and illustrations are available royalty-free.

Brainbow mouse Harvard University scientists made a neuroimaging breakthrough in when they developed the Brainbow technique. First demonstrated in a transgenic mouse, the method allows whole arrays of similar neurons in a brain to be distinguished from one another through different combinations of fluorescently colored proteins. Images resulting from the technique are digitally recolored to enhance the contrast between cells and map the complex interconnections in the nervous system. As this image demonstrates, Brainbow technique can make for striking images; some have won awards in science photography competitions.

Cast of blood vessels This striking resin model of the brain's blood vessels could win an art award of its own. To make a cast like this, the vascular system of an animal or organ can be injected with liquid plastic that fills the blood space and rapidly solidifies. Acid or alkaline solution is then used to corrode the surrounding tissue, leaving a hardened cast that accurately represents the original vascular system and can be examined with electron microscopes.

Joseph Towne wax model A wax model of the brain by Joseph Towne, known as one of the most skilled makers of wax medical models of the 19th century, as well as a talented marble sculptor.